Triple
T12602098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MNR |
E300881
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | MNR |
unclear NED1
|
NE FINISHED |
How this triple was built (2 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: [MNR, shortName, MNR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MNR Context triple: [MNR, shortName, MNR]
-
A.
MNR
MNR is the abbreviated designation for the National Republican Navy, the maritime military force of the Italian Social Republic during World War II.
-
B.
MNR
MNR is the central government ministry of China responsible for managing the country’s natural resources, including land, minerals, and maritime areas.
-
C.
MNIR
MNIR is the commonly used abbreviation for the National Museum of Romanian History, a major institution in Bucharest dedicated to preserving and showcasing Romania’s historical and cultural heritage.
-
D.
MNI
MNI is the IATA airport code for John A. Osborne Airport on the Caribbean island of Montserrat.
-
E.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (3 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d1f6ac8190ab21ca7bcbc80129 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec92c6c8190bd2d193e70940407 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:09 p.m.