Triple
T2528403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marymount School of New York |
E56093
|
entity |
| Predicate | hasReligiousLifeProgram |
P31599
|
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, hasReligiousLifeProgram, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousLifeProgram Context triple: [Marymount School of New York, hasReligiousLifeProgram, true]
-
A.
hasReligiousOrganization
Indicates that an entity is associated with, governed by, or belongs to a specific religious organization.
-
B.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
C.
hasChapelProgram
chosen
Indicates that an institution or organization offers or conducts a chapel program as part of its activities or services.
-
D.
hasReligiousSponsor
Indicates that an entity is financially or organizationally supported by a religious individual, group, or institution.
-
E.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
- 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.