Triple
T33089986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Goldman |
E846751
|
entity |
| Predicate | characterInWorkSetInTimePeriod |
P119878
|
FINISHED |
| Object | 1980s |
—
|
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: 1980s | Statement: [Jessica Goldman, characterInWorkSetInTimePeriod, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInWorkSetInTimePeriod Context triple: [Jessica Goldman, characterInWorkSetInTimePeriod, 1980s]
-
A.
characterInPeriod
chosen
Indicates that a character exists or is active during a specified historical or temporal period.
-
B.
isContemporaryOfFictionalCharacter
Indicates that one entity exists or occurs in the same fictional time period as another fictional character.
-
C.
isCharacterInWork
Indicates that a particular character appears in or is part of a specified creative work (such as a book, film, or game).
-
D.
genreOfWorkCharacterIsIn
Indicates the specific genre of the creative work in which a given character appears.
-
E.
characterCreatedInYear
Indicates the specific calendar year in which a fictional or narrative character was first created or introduced.
- 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_69ff234f32888190a1d800a3bda432eb |
completed | May 9, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_69ff228ae9a0819083f4b97c10b923f4 |
completed | May 9, 2026, 12:03 p.m. |
Created at: May 1, 2026, 1:26 a.m.