Triple
T38037084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | גבעת שמואל |
E949379
|
entity |
| Predicate | כוללת מוסד אקדמי סמוך |
P159284
|
FINISHED |
| Object | אוניברסיטת בר-אילן |
—
|
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 בר-אילן | Statement: [גבעת שמואל, כוללת מוסד אקדמי סמוך, אוניברסיטת בר-אילן]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: כוללת מוסד אקדמי סמוך Context triple: [גבעת שמואל, כוללת מוסד אקדמי סמוך, אוניברסיטת בר-אילן]
-
A.
כולל מוסד אקדמי
chosen
Indicates that something contains, encompasses, or incorporates an academic institution as one of its components or members.
-
B.
adjacentToCampusOf
Indicates that one entity is located next to or directly bordering the campus area of another entity.
-
C.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
D.
nearCampusAcademicFocus
Indicates that an entity is located close to a campus and is primarily oriented toward academic or educational activities associated with that campus.
-
E.
hasNearbyInstitutionType
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
- 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_69f76eff0bb0819084bc4e63997bd039 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.