Triple
T4280367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Brute |
E97132
|
entity |
| Predicate | dramaticGenreRole |
P32515
|
FINISHED |
| Object | comic but serious figure |
—
|
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: comic but serious figure | Statement: [Lady Brute, dramaticGenreRole, comic but serious figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dramaticGenreRole Context triple: [Lady Brute, dramaticGenreRole, comic but serious figure]
-
A.
dramaticRole
Indicates that one entity serves as a character or part played by another entity within a dramatic or theatrical work.
-
B.
dramaticCharacter
Indicates that one entity is a character or role that appears within the dramatic work, performance, or narrative represented by the other entity.
-
C.
theaterRole
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
-
D.
genreRole
chosen
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
-
E.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35037b654819087abbb5ea231eefd |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.