Triple
T35199372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shooter film universe |
E1016354
|
entity |
| Predicate | sharesProtagonistNameWith |
P20785
|
FINISHED |
| Object | Bob Lee Swagger (novel series character) |
—
|
NE NERFINISHED |
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: Bob Lee Swagger (novel series character) | Statement: [Shooter film universe, sharesProtagonistNameWith, Bob Lee Swagger (novel series character)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesProtagonistNameWith Context triple: [Shooter film universe, sharesProtagonistNameWith, Bob Lee Swagger (novel series character)]
-
A.
sharesProtagonistWith
Indicates that two narrative works feature the same main protagonist character.
-
B.
sharesCharacterWith
Indicates that two entities have at least one character (such as a letter, symbol, or glyph) in common.
-
C.
protagonistNameSharedByTwoCharacters
Indicates that two distinct characters share the same protagonist name.
-
D.
sharesFilmWithCharacter
Indicates that one character appears in or is associated with at least one film that another specified character also appears in.
-
E.
sharesGivenNameWith
chosen
Indicates that two entities have the same given (first) name.
- 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_69f76dde814c8190a71f60d514a424a4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00512437d48190ad20324968ead5f4 |
completed | May 10, 2026, 9:34 a.m. |
| PD | Predicate disambiguation | batch_6a0050227350819099f41369c3d168be |
completed | May 10, 2026, 9:30 a.m. |
Created at: May 3, 2026, 4:02 p.m.