Triple
T1044051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man with the Golden Gun |
E22534
|
entity |
| Predicate | notableWeapon |
P7745
|
FINISHED |
| Object | golden gun |
—
|
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: golden gun | Statement: [The Man with the Golden Gun, notableWeapon, golden gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWeapon Context triple: [The Man with the Golden Gun, notableWeapon, golden gun]
-
A.
typicalWeapon
chosen
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
B.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
C.
weapon
Indicates that one entity is used as a weapon by, or serves as the weapon of, another entity.
-
D.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
E.
notableAttack
Indicates that an entity carried out, was involved in, or is strongly associated with a particularly significant or well-known attack.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8475ab48190848388eea6448cb6 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.