Triple
T36725924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airman’s Medal |
E907195
|
entity |
| Predicate | wearsWithUniform |
P18730
|
FINISHED |
| Object | United States Air Force uniform |
—
|
LITERAL 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: United States Air Force uniform | Statement: [Airman’s Medal, wearsWithUniform, United States Air Force uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsWithUniform Context triple: [Airman’s Medal, wearsWithUniform, United States Air Force uniform]
-
A.
wearsOnUniform
chosen
Indicates that an item is part of and is worn as a component of a uniform.
-
B.
woreUniformOf
Indicates that one entity was dressed in or used the official uniform associated with another entity (such as an organization, group, or role).
-
C.
wearsUniformColor
Indicates that an entity regularly uses or is associated with a specific uniform color as part of its standard attire or dress code.
-
D.
wearsUniformSimilarTo
Indicates that one entity wears a uniform that is similar in appearance or style to the uniform worn by another entity.
-
E.
mayWearUniform
Indicates that an entity is permitted or authorized to wear a particular uniform in a given context.
- F. None of above.
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_69f76e746e4c8190a0d05cc6d57a643e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.