Triple
T35149003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bishop’s Wife |
E1014930
|
entity |
| Predicate | DavidNivenRole |
P182334
|
FINISHED |
| Object | Bishop Henry Brougham |
—
|
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: Bishop Henry Brougham | Statement: [The Bishop’s Wife, DavidNivenRole, Bishop Henry Brougham]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DavidNivenRole Context triple: [The Bishop’s Wife, DavidNivenRole, Bishop Henry Brougham]
-
A.
directorCharacterName
Indicates that the specified name is the character name used by the director (or representing the director) within a work.
-
B.
humphreyBogartRole
Indicates that one entity is a role or character portrayed by Humphrey Bogart in a film, play, or other performance.
-
C.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
D.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
-
E.
roleInFamousPlay
Indicates that an entity portrays or has portrayed a specific character in a well-known theatrical play.
- F. None of above. chosen
Provenance (4 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78cea708c8190a2702c9825b6b094 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.