Triple
T33804718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonny Goodman |
E866347
|
entity |
| Predicate | hasReligionInSeriesContext |
P83945
|
FINISHED |
| Object | Jewish background |
—
|
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: Jewish background | Statement: [Jonny Goodman, hasReligionInSeriesContext, Jewish background]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionInSeriesContext Context triple: [Jonny Goodman, hasReligionInSeriesContext, Jewish background]
-
A.
hasMainReligionContext
Indicates that one entity serves as the primary religious context, tradition, or framework associated with another entity.
-
B.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
C.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
D.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
E.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
- 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_69f3499057fc81909d862b1309a3bd71 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:46 a.m.