Triple
T10338441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Robinson |
E243065
|
entity |
| Predicate | isTitleCharacterReference |
P46756
|
FINISHED |
| Object | character Mrs. Robinson from The Graduate |
—
|
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: character Mrs. Robinson from The Graduate | Statement: [Mrs. Robinson, isTitleCharacterReference, character Mrs. Robinson from The Graduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTitleCharacterReference Context triple: [Mrs. Robinson, isTitleCharacterReference, character Mrs. Robinson from The Graduate]
-
A.
isTitleCharacterString
Indicates that a given string represents the title text associated with an entity.
-
B.
isTitleFor
Indicates that one entity serves as the official title or name designation for another entity.
-
C.
starIsTitleCharacter
Indicates that the referenced star is the main or title character of the work in question.
-
D.
hasTitleCharacterRelation
chosen
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
E.
hasTitleCharacterLocation
Indicates that a title or heading is associated with a specific character’s location within a text or media.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e91fdb2081909866c6ecf417d75a |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:54 a.m.