Triple
T2391544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Republican Navy |
E48954
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
MNR
MNR is the abbreviated designation for the National Republican Navy, the maritime military force of the Italian Social Republic during World War II.
|
E263565
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: MNR | Statement: [National Republican Navy, shortName, MNR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MNR Context triple: [National Republican Navy, shortName, MNR]
-
A.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
-
B.
MR
MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
-
C.
MR
MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
-
D.
MNP
MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
-
E.
MRF
MRF (Media Resource Function) is a core network component in IP Multimedia Subsystem (IMS) architectures responsible for handling media processing tasks such as mixing, transcoding, and media stream manipulation for real-time communication services.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MNR Triple: [National Republican Navy, shortName, MNR]
Generated description
MNR is the abbreviated designation for the National Republican Navy, the maritime military force of the Italian Social Republic during World War II.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MNR Target entity description: MNR is the abbreviated designation for the National Republican Navy, the maritime military force of the Italian Social Republic during World War II.
-
A.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
-
B.
MR
MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
-
C.
MR
MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
-
D.
MNP
MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
-
E.
MRF
MRF (Media Resource Function) is a core network component in IP Multimedia Subsystem (IMS) architectures responsible for handling media processing tasks such as mixing, transcoding, and media stream manipulation for real-time communication services.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87457388190822d5506327db8f2 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3d7b4908190a87dd33316d2d725 |
completed | March 9, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_69aeb4b83ec48190b2852daef0767ac8 |
completed | March 9, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeb57af28c8190bfca30ad3e7ca8b3 |
completed | March 9, 2026, 11:56 a.m. |
Created at: March 4, 2026, 7:57 p.m.