Triple
T35384230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shooter (novel) |
E1022738
|
entity |
| Predicate | characterRoleOfBobLeeSwagger |
P192169
|
FINISHED |
| Object | former Marine sniper |
—
|
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: former Marine sniper | Statement: [Shooter (novel), characterRoleOfBobLeeSwagger, former Marine sniper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfBobLeeSwagger Context triple: [Shooter (novel), characterRoleOfBobLeeSwagger, former Marine sniper]
-
A.
leadActorForCharacter Buz Murdock
Indicates that the specified person is the primary actor portraying the character Buz Murdock.
-
B.
describesCharacterRole
chosen
Indicates that one entity specifies or defines the narrative or functional role played by another entity.
-
C.
roleInCobraKai
Indicates that an entity has a specific role or position within the context of Cobra Kai.
-
D.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
E.
filmCharacterDescribedAs
Indicates that a film character is described or characterized using a particular attribute, phrase, or depiction.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff97637ad881908c24fe2cc6b036db |
completed | May 9, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69ff96c43a808190942eeda1934602db |
completed | May 9, 2026, 8:19 p.m. |
Created at: May 3, 2026, 4:03 p.m.