Triple
T36589891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | יצחק הרצוג |
E902638
|
entity |
| Predicate | מוסד לימודים |
P108926
|
FINISHED |
| Object | אוניברסיטת תל אביב |
—
|
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: אוניברסיטת תל אביב | Statement: [יצחק הרצוג, מוסד לימודים, אוניברסיטת תל אביב]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: מוסד לימודים Context triple: [יצחק הרצוג, מוסד לימודים, אוניברסיטת תל אביב]
-
A.
schoolOf
chosen
Indicates that an educational institution is the one where a person studied, worked, or is otherwise academically affiliated.
-
B.
isEducationalCenterOf
Indicates that an institution functions as the primary educational center serving, representing, or associated with a particular area, organization, or group.
-
C.
ultimateInstitution
Indicates that one institution is the highest-level or final authoritative institution in relation to another entity or context.
-
D.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
E.
educationFacility
Indicates that one entity functions as an institution or place where the other entity receives or provides education or training.
- 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_69f76e6592e88190bac4eb00a46e9df9 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.