Triple
T26512485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 101st Airborne Division shoulder sleeve insignia |
E669719
|
entity |
| Predicate | isDistinctiveUnitInsignia |
P160805
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [101st Airborne Division shoulder sleeve insignia, isDistinctiveUnitInsignia, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDistinctiveUnitInsignia Context triple: [101st Airborne Division shoulder sleeve insignia, isDistinctiveUnitInsignia, false]
-
A.
wearsInsigniaAt
Indicates that an entity is wearing or displaying a particular insignia at a specified location or point in time.
-
B.
hasMilitaryDesignation
Indicates that an entity is assigned a specific military-related code, title, or classification.
-
C.
hasDistinctiveEmblem
Indicates that an entity possesses a unique symbol, logo, or emblem that serves to distinguish it from others.
-
D.
isNamedMilitaryUnit
Indicates that the subject is a military unit that has been given a specific official name.
-
E.
usArmyDesignation
Indicates the specific designation or code assigned to something by the United States Army.
- F. None of above. chosen
Provenance (4 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61393bbb881908e8394604afdb144 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f604120e848190b516c29b781d19cc |
completed | May 2, 2026, 2:02 p.m. |
Created at: April 27, 2026, 1:21 a.m.