Triple
T2120370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duel at Diablo |
E43905
|
entity |
| Predicate | hasGunfights |
P34956
|
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: [Duel at Diablo, hasGunfights, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGunfights Context triple: [Duel at Diablo, hasGunfights, true]
-
A.
battledIn
Indicates that two or more entities engaged in a battle or conflict that took place at a specific location or during a particular event.
-
B.
shootsAgainst
Indicates that one entity fires a projectile or weapon in the direction of, or in opposition to, another entity.
-
C.
fightingOutOf
Indicates that an individual is competing or representing themselves in a fight or match while being officially associated with a particular location, camp, or organization.
-
D.
fought
Indicates that one entity engaged in physical or armed conflict or combat against another entity.
-
E.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb3404348190bc843022fbd2b4d0 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:44 p.m.