Triple
T38107660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I’ll Never Have That Chance |
E951563
|
entity |
| Predicate | hasTitleCharacterPerspective |
P46756
|
FINISHED |
| Object | Lestat de Lioncourt |
—
|
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: Lestat de Lioncourt | Statement: [I’ll Never Have That Chance, hasTitleCharacterPerspective, Lestat de Lioncourt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleCharacterPerspective Context triple: [I’ll Never Have That Chance, hasTitleCharacterPerspective, Lestat de Lioncourt]
-
A.
hasTitleCharacterTrait
Indicates that a title is associated with a specific character trait of an entity.
-
B.
hasTitleCharacterAction
Indicates that a work’s title explicitly references or is derived from an action performed by a character within that work.
-
C.
hasTitleCharacterRelation
chosen
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
D.
hasTitleCharacterLocation
Indicates that a title or heading is associated with a specific character’s location within a text or media.
-
E.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
- 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_69f76f065ed08190bdfb1b6d817f5b39 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: May 3, 2026, 4:21 p.m.