Triple
T31212914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Django (1966 film) |
E795796
|
entity |
| Predicate | leadCharacterWeapon |
P127038
|
FINISHED |
| Object | machine gun hidden in coffin |
—
|
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: machine gun hidden in coffin | Statement: [Django (1966 film), leadCharacterWeapon, machine gun hidden in coffin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterWeapon Context triple: [Django (1966 film), leadCharacterWeapon, machine gun hidden in coffin]
-
A.
titleCharacterWeapon
chosen
Indicates that a weapon is the primary or signature armament associated with a story’s title character.
-
B.
armedBy
Indicates that one entity is supplied with weapons, equipment, or armaments by another entity.
-
C.
weaponryCarried
Indicates that one entity is carrying or equipped with a weapon or set of weapons in relation to another entity or context.
-
D.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
E.
facedWeapon
Indicates that one entity confronted, opposed, or dealt with another entity while that other entity was armed with a weapon.
- 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_69f224d9d52c8190a61f68ded37fa755 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c28a0e4819099600420cd0da971 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f696673214819094350e1d2648ef34 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:09 p.m.