Triple
T2528410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marymount School of New York |
E56093
|
entity |
| Predicate | hasReligiousChapel |
P34531
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Marymount School of New York, hasReligiousChapel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousChapel Context triple: [Marymount School of New York, hasReligiousChapel, true]
-
A.
hasChapels
chosen
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
B.
hasPlaceOfWorship
Indicates that an entity possesses, contains, or is associated with a designated location used for religious or spiritual worship.
-
C.
hasClericalStructure
Indicates that an entity possesses an organized clerical or administrative hierarchy or framework.
-
D.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
E.
hasCathedralDenomination
Indicates the religious denomination with which a cathedral is affiliated or to which it belongs.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd257ea908190a010c0b785853546 |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.