Triple
T15063564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hard Target |
E379697
|
entity |
| Predicate | hasGunFuElements |
P117173
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hard Target, hasGunFuElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGunFuElements Context triple: [Hard Target, hasGunFuElements, true]
-
A.
hasBlackBeltIn
Indicates that an entity holds a black belt rank or equivalent high-level certification in a specified martial art or discipline.
-
B.
hasGunfights
Indicates that there are one or more gunfights occurring between the related entities.
-
C.
isGrapplingArt
Indicates that the subject is a martial art or combat style primarily focused on grappling techniques such as holds, locks, and throws.
-
D.
hasStunts
Indicates that one entity performs, includes, or is associated with stunt actions for another entity or context.
-
E.
hasFightingStance
Indicates that an entity adopts or is characterized by a particular combat or fighting posture.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee803ac81908bb7d66e49c2eb72 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:02 a.m.