Triple
T33089985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Goldman |
E846751
|
entity |
| Predicate | characterInWorkSetIn |
P176973
|
FINISHED |
| Object | Manhattan |
—
|
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: Manhattan | Statement: [Jessica Goldman, characterInWorkSetIn, Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInWorkSetIn Context triple: [Jessica Goldman, characterInWorkSetIn, Manhattan]
-
A.
isCharacterInWork
chosen
Indicates that a particular character appears in or is part of a specified creative work (such as a book, film, or game).
-
B.
composerOfWorkFeaturingCharacter
Indicates that one entity is the composer of a musical or dramatic work in which the other entity appears as a character.
-
C.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
D.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
E.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff21cbd9108190a52c0ba42004c669 |
completed | May 9, 2026, noon |
| PD | Predicate disambiguation | batch_69ff1faea91881908c626c70bca5100a |
completed | May 9, 2026, 11:51 a.m. |
Created at: May 1, 2026, 1:26 a.m.