Triple
T19741477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Tasker |
E474130
|
entity |
| Predicate | hasWeaponUse |
P706
|
FINISHED |
| Object | uses firearms during climax of 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: uses firearms during climax of film | Statement: [Helen Tasker, hasWeaponUse, uses firearms during climax of film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeaponUse Context triple: [Helen Tasker, hasWeaponUse, uses firearms during climax of film]
-
A.
usedWeapon
chosen
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
B.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
C.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
D.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
-
E.
hasArtilleryUse
Indicates that one entity employs, operates, or makes use of artillery in relation to another entity 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6516159c8819090022094aa91902b |
completed | April 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.