Triple
T28260069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Mamelles de Tirésias |
E712558
|
entity |
| Predicate | mainFemaleProtagonist |
P9202
|
FINISHED |
| Object | Thérèse |
—
|
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: Thérèse | Statement: [Les Mamelles de Tirésias, mainFemaleProtagonist, Thérèse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainFemaleProtagonist Context triple: [Les Mamelles de Tirésias, mainFemaleProtagonist, Thérèse]
-
A.
mainProtagonist
chosen
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
B.
hasFemaleAntagonistProtagonist
Indicates that the work features both a female antagonist and a female protagonist in central opposing roles.
-
C.
protagonistGenderSelectable
Indicates that the gender of the story’s main character can be chosen or customized by the player or user.
-
D.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
-
E.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64417c3f081908eb1950a94b7be65 |
completed | May 2, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:11 p.m.