Triple
T1823244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borough Park |
E40588
|
entity |
| Predicate | hasReligiousInstitutionType |
P31566
|
FINISHED |
| Object | yeshiva |
—
|
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: yeshiva | Statement: [Borough Park, hasReligiousInstitutionType, yeshiva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousInstitutionType Context triple: [Borough Park, hasReligiousInstitutionType, yeshiva]
-
A.
hasReligiousOrganization
Indicates that an entity is associated with, governed by, or belongs to a specific religious organization.
-
B.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
C.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
D.
hasCathedralDenomination
Indicates the religious denomination with which a cathedral is affiliated or to which it belongs.
-
E.
isPlaceOfWorshipFor
Indicates that a location serves as a site where members of a particular religion or belief system perform worship or religious practices.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab21ab83a48190a33afe5db19a21f8 |
completed | March 6, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61d97d008190b6642aef32eb7e36 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab21aa56108190a5123539d5020741 |
completed | March 6, 2026, 6:49 p.m. |
Created at: March 4, 2026, 7:32 p.m.