Triple
T15659759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dybbuk |
E376537
|
entity |
| Predicate | religiousFigureCharacter |
P70093
|
FINISHED |
| Object | tzaddik |
—
|
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: tzaddik | Statement: [The Dybbuk, religiousFigureCharacter, tzaddik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousFigureCharacter Context triple: [The Dybbuk, religiousFigureCharacter, tzaddik]
-
A.
religiousFigure
Indicates that one entity is recognized or designated as a religious leader, authority, or sacred person in relation to another entity.
-
B.
religiousFigureType
chosen
Indicates the specific role or category of a person recognized as a religious figure (e.g., priest, monk, prophet) within a religious context.
-
C.
religiousTextRole
Indicates the specific role or function that a religious text has in relation to a person, group, practice, or tradition.
-
D.
religionOfCharacterPortrayed
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
E.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef4e6a08190ad8bbafaa3612f22 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.