Triple
T31563824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Harrington |
E805346
|
entity |
| Predicate | aliasesInFilm |
P166014
|
FINISHED |
| Object | Lady Eve Sidwich |
—
|
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: Lady Eve Sidwich | Statement: [Jean Harrington, aliasesInFilm, Lady Eve Sidwich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aliasesInFilm Context triple: [Jean Harrington, aliasesInFilm, Lady Eve Sidwich]
-
A.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
-
B.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
C.
bondActorInFilm
Indicates that the person is an actor who has portrayed the character James Bond in a film.
-
D.
placementInFilm
Indicates the specific position or occurrence of something within the sequence or structure of a film.
-
E.
alsoAppearsAs
chosen
Indicates that an entity is known or presented under an alternative name, form, or representation.
- 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_69f348d2ee94819091918d1789398c29 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8055f8081908f635fe04654b5fe |
completed | May 3, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:16 p.m.