Triple
T32936839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regan Reilly |
E842553
|
entity |
| Predicate | characterInSeriesBy |
P110595
|
FINISHED |
| Object | Carol Higgins Clark |
—
|
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: Carol Higgins Clark | Statement: [Regan Reilly, characterInSeriesBy, Carol Higgins Clark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInSeriesBy Context triple: [Regan Reilly, characterInSeriesBy, Carol Higgins Clark]
-
A.
characterInBookBy
chosen
Indicates that a character appears in a book that was written by a specified author.
-
B.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
C.
characterInFilmSeries
Indicates that a character appears in or is part of the cast of a particular film series.
-
D.
characterInPlayBy
Indicates that a character appears in or is part of a play authored or created by a specific person.
-
E.
characterAppearsIn
Indicates that a specific character is present or featured within a particular work, such as a book, movie, or episode.
- 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_69f34949727c81909d195c97de3341c8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
Created at: May 1, 2026, 1:20 a.m.