Triple
T25339580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Have and to Hold (1916 film) |
E635371
|
entity |
| Predicate | mainCharacterFromSourceWork |
P146684
|
FINISHED |
| Object | Lady Jocelyn Leigh |
—
|
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 Jocelyn Leigh | Statement: [To Have and to Hold (1916 film), mainCharacterFromSourceWork, Lady Jocelyn Leigh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterFromSourceWork Context triple: [To Have and to Hold (1916 film), mainCharacterFromSourceWork, Lady Jocelyn Leigh]
-
A.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
B.
hasProtagonistFromSource
Indicates that a work’s main character originates from, or is derived from, a specified source (such as another work, franchise, or medium).
-
C.
narrativeSourceCharacter
Indicates that a particular character serves as the source or narrator from whose perspective the narrative is presented.
-
D.
hasMainCharacterFrom
chosen
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
E.
mainCharacterCodeNumber
Indicates that an entity is identified as the primary or central character by a specific code number.
- 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 21, 2026, 1:32 p.m.