Triple
T35881879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tank Destruction Badge |
E1037531
|
entity |
| Predicate | weaponExamples |
P184220
|
FINISHED |
| Object | hand grenade |
—
|
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: hand grenade | Statement: [Tank Destruction Badge, weaponExamples, hand grenade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weaponExamples Context triple: [Tank Destruction Badge, weaponExamples, hand grenade]
-
A.
weaponsRepresent
Indicates that certain weapons serve as symbols or embodiments of something, such as ideas, groups, or values.
-
B.
weaponsBay
Indicates that one entity serves as the weapons bay (storage or housing area for weapons) of another entity.
-
C.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
D.
weaponOfInterest
Indicates that an entity is a weapon that is specifically relevant, notable, or targeted for attention within a given context or scenario.
-
E.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
- 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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:06 p.m.