Triple
T35640749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zangief |
E1029851
|
entity |
| Predicate | combatRangeSpecialty |
P183574
|
FINISHED |
| Object | close range |
—
|
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: close range | Statement: [Zangief, combatRangeSpecialty, close range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatRangeSpecialty Context triple: [Zangief, combatRangeSpecialty, close range]
-
A.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
-
B.
hasFiringRange
Indicates that one entity possesses or provides a designated area or capability for discharging weapons over a specified distance.
-
C.
specialForcesInvolved
Indicates that special forces units participate in or are involved in the referenced action, event, or operation.
-
D.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
E.
combatApplication
Indicates the application or use of something (such as skills, tactics, or equipment) within a combat or fighting context.
- 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_69f76e087bdc8190a4794bf9c0bd7634 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:05 p.m.