Triple
T12317066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Cohn |
E293628
|
entity |
| Predicate | religionOrEthnicityInFiction |
P83945
|
FINISHED |
| Object | Jewish |
—
|
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 | Statement: [Robert Cohn, religionOrEthnicityInFiction, Jewish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionOrEthnicityInFiction Context triple: [Robert Cohn, religionOrEthnicityInFiction, Jewish]
-
A.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
B.
hasNameInReligionOrFolklore
Indicates that an entity is known by a particular name specifically within a religious or folkloric tradition.
-
C.
fictionalEthnoCulturalIdentity
Indicates that an entity is associated with an invented or imaginary ethnic or cultural identity, rather than a real-world one.
-
D.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
E.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.