Triple
T34696318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chon |
E891039
|
entity |
| Predicate | combatBackground |
P61941
|
FINISHED |
| Object | Iraq War veteran (implied in film) |
—
|
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: Iraq War veteran (implied in film) | Statement: [Chon, combatBackground, Iraq War veteran (implied in film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatBackground Context triple: [Chon, combatBackground, Iraq War veteran (implied in film)]
-
A.
combatView
Indicates a perspective or representation of entities engaged in combat or battle-related interaction.
-
B.
combat
Indicates that two or more entities are engaged in fighting or armed conflict with each other.
-
C.
combatBy
Indicates a relationship where one entity engages in combat or fighting through the agency, actions, or involvement of another entity.
-
D.
combatRelated
chosen
Indicates that the entities are connected through participation in, involvement with, or direct association to combat or military conflict.
-
E.
battlegroundFor
Indicates that a location serves as the site or arena where a conflict, competition, or struggle between entities takes place.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7237f53488190a70af2cc56d0e5ca |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:05 a.m.