Triple
T38593265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tactical Visor |
E932501
|
entity |
| Predicate | teamRoleContext |
P40371
|
FINISHED |
| Object | Damage dealing and securing eliminations |
—
|
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: Damage dealing and securing eliminations | Statement: [Tactical Visor, teamRoleContext, Damage dealing and securing eliminations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamRoleContext Context triple: [Tactical Visor, teamRoleContext, Damage dealing and securing eliminations]
-
A.
teamContext
Indicates that an entity is considered or interpreted within the scope, structure, or circumstances of a particular team.
-
B.
roleSynergy
Indicates how effectively two or more roles complement and enhance each other’s performance when combined.
-
C.
roleInPersonnelMatters
Indicates that one entity has a specific function, authority, or involvement in managing or deciding personnel-related matters concerning another entity.
-
D.
teamDynamic
Indicates how members of a group interact, collaborate, and influence each other’s behavior and performance as a collective unit.
-
E.
unitRole
chosen
Indicates the functional role or purpose that a unit serves within a larger system or 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.