Triple
T32657777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebellious Rabbi |
E834907
|
entity |
| Predicate | subjectLaterNationality |
P191813
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Rebellious Rabbi, subjectLaterNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectLaterNationality Context triple: [Rebellious Rabbi, subjectLaterNationality, American]
-
A.
titleHolderLaterNationality
Indicates that the person who held a particular title later acquired or changed to the specified nationality.
-
B.
nationalityAfterEmigration
Indicates the nationality a person acquires or holds after emigrating from their original country.
-
C.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
D.
userNationality
Indicates that a user has a specific national affiliation or citizenship.
-
E.
originalAuthorLaterNationality
Indicates that the original author of a work later acquired or changed to the specified nationality.
- F. None of above. chosen
Provenance (4 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_69f3492f72248190ba42fa596aea50e1 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
| PDg | Predicate description generation | batch_69fcec5e560481909cd710b88897e833 |
completed | May 7, 2026, 7:47 p.m. |
Created at: May 1, 2026, 1:08 a.m.