Triple
T35977903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babylonian Talmudic academies |
E1040473
|
entity |
| Predicate | hadMajorAcademy |
P65904
|
FINISHED |
| Object | Sura academy |
—
|
NE NERFINISHED |
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: Sura academy | Statement: [Babylonian Talmudic academies, hadMajorAcademy, Sura academy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMajorAcademy Context triple: [Babylonian Talmudic academies, hadMajorAcademy, Sura academy]
-
A.
majorSchool
chosen
Indicates that one entity is the primary or most significant school or educational institution associated with another entity.
-
B.
hasMajorUniversity
Indicates that a location or region contains at least one prominent, large, or academically significant university.
-
C.
hasAcademy
Indicates that an entity possesses, operates, or is formally associated with an academy as part of its structure or offerings.
-
D.
containsMilitaryAcademy
Indicates that one entity includes or hosts a military academy within its boundaries or domain.
-
E.
hadInstitution
Indicates that an entity was affiliated with, operated within, or was served by a particular institution during some period of time.
- 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_69f76e27758c81909b711cf38a130aaf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.