Triple
T6447835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belz |
E139785
|
entity |
| Predicate | hasEducationalNetwork |
P28186
|
FINISHED |
| Object | yeshivas and Talmud Torah schools |
—
|
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: yeshivas and Talmud Torah schools | Statement: [Belz, hasEducationalNetwork, yeshivas and Talmud Torah schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalNetwork Context triple: [Belz, hasEducationalNetwork, yeshivas and Talmud Torah schools]
-
A.
educationalNetworkName
Indicates the name of an educational network with which an entity is associated.
-
B.
hasAssociatedSchoolNetwork
chosen
Indicates that an entity is linked to or belongs to a particular school network or group of affiliated schools.
-
C.
hasEducationDomain
Indicates that an entity is associated with or operates within a specific educational domain or field of study.
-
D.
hasEducationalLink
Indicates that there is an educational relationship or connection between two entities, such as teaching, learning, training, or academic affiliation.
-
E.
containsEducationalInstitution
Indicates that one entity geographically or administratively includes or encompasses an educational institution within its boundaries or structure.
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069afd8c48190b3cab580c813ecab |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:47 p.m.