Triple
T35881877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tank Destruction Badge |
E1037531
|
entity |
| Predicate | multipleAwards |
P3160
|
FINISHED |
| Object | one silver badge per tank destroyed |
—
|
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: one silver badge per tank destroyed | Statement: [Tank Destruction Badge, multipleAwards, one silver badge per tank destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multipleAwards Context triple: [Tank Destruction Badge, multipleAwards, one silver badge per tank destroyed]
-
A.
hasMultipleAwardsIndicatedBy
Indicates that an entity is recognized as having received multiple awards, as evidenced or signaled by a specified source or indicator.
-
B.
numberOfAwards
chosen
Indicates the total count of awards that have been received by an entity.
-
C.
alsoAwardedIn
Indicates that the same award or recognition was given in an additional time, place, or context beyond the primary one.
-
D.
notableMultipleAwardWinnersAlsoWon
Indicates that entities who are notable multiple award winners have also won an additional specified award.
-
E.
occasionOfAwards
Indicates that an event or circumstance serves as the context or setting in which certain awards are given or presented.
- 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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:06 p.m.