Triple
T34965634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armadale |
E1008386
|
entity |
| Predicate | hasFemaleVillain |
P32100
|
FINISHED |
| Object | Lydia Gwilt |
—
|
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: Lydia Gwilt | Statement: [Armadale, hasFemaleVillain, Lydia Gwilt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemaleVillain Context triple: [Armadale, hasFemaleVillain, Lydia Gwilt]
-
A.
hasFemaleAntagonistProtagonist
Indicates that the work features both a female antagonist and a female protagonist in central opposing roles.
-
B.
hasVillain
chosen
Indicates that one entity is the villain or primary antagonist associated with another entity.
-
C.
hasFemmeFataleCharacter
Indicates that a work includes a femme fatale character who plays a significant role in the narrative.
-
D.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
E.
hasFemaleCharacter
Indicates that an entity includes or features at least one female 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4 p.m.