Triple
T4553121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMIRS |
E120415
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MMIRS
MMIRS is a near-infrared spectrograph and imager used on large telescopes for astronomical observations in the infrared spectrum.
|
E451581
|
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: MMIRS | Statement: [MMIRS, abbreviation, MMIRS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MMIRS Context triple: [MMIRS, abbreviation, MMIRS]
-
A.
MIR
MIR is the commonly used abbreviation for "Men in Red," typically referring to a sports team or group distinguished by their red uniforms.
-
B.
MM
MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
-
C.
MMI
MMI is an abbreviation for Muslim Mosque, Inc., a religious organization associated with the Muslim community.
-
D.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
-
E.
IMM
IMM is a research organization focused on advancing molecular nanotechnology and atomically precise manufacturing.
- 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: MMIRS Triple: [MMIRS, abbreviation, MMIRS]
Generated description
MMIRS is a near-infrared spectrograph and imager used on large telescopes for astronomical observations in the infrared spectrum.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MMIRS Target entity description: MMIRS is a near-infrared spectrograph and imager used on large telescopes for astronomical observations in the infrared spectrum.
-
A.
MIR
MIR is the commonly used abbreviation for "Men in Red," typically referring to a sports team or group distinguished by their red uniforms.
-
B.
MM
MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
-
C.
MMI
MMI is an abbreviation for Muslim Mosque, Inc., a religious organization associated with the Muslim community.
-
D.
MRS
MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
-
E.
IMM
IMM is a research organization focused on advancing molecular nanotechnology and atomically precise manufacturing.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd581160e08190b715a8ce5c3e6c9b |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdb95b01b0819094a600752e41aa09 |
completed | March 20, 2026, 9:17 p.m. |
| NEDg | Description generation | batch_69bdbdbf73508190b64a78ff9274ee6d |
completed | March 20, 2026, 9:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdbe1bcd8c819094adea59c91c6f5b |
completed | March 20, 2026, 9:37 p.m. |
Created at: March 20, 2026, 1:09 p.m.