Triple
T27814058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple Sinai of Brookline |
E702609
|
entity |
| Predicate | hasReligionCategory |
P104709
|
FINISHED |
| Object | Reform synagogue |
—
|
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: Reform synagogue | Statement: [Temple Sinai of Brookline, hasReligionCategory, Reform synagogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionCategory Context triple: [Temple Sinai of Brookline, hasReligionCategory, Reform synagogue]
-
A.
hasReligiousType
chosen
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
B.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
C.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
D.
recognizesReligion
Indicates that one entity formally acknowledges or accepts another entity as a valid or legitimate religion.
-
E.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff0b6bc4a88190bf1d38c6ea26bcdc |
completed | May 9, 2026, 10:24 a.m. |
| PD | Predicate disambiguation | batch_69ff082a22f4819095ded971dbd8ea7b |
completed | May 9, 2026, 10:10 a.m. |
Created at: April 27, 2026, 5:44 p.m.