Triple
T28072905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishtar Park |
E709453
|
entity |
| Predicate | namedForPersonReligion |
P173237
|
FINISHED |
| Object | Muslim |
—
|
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: Muslim | Statement: [Nishtar Park, namedForPersonReligion, Muslim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForPersonReligion Context triple: [Nishtar Park, namedForPersonReligion, Muslim]
-
A.
associatedReligionRole
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
-
B.
hasReligiousAffiliationInName
Indicates that an entity’s name explicitly includes or reflects a religious affiliation or association.
-
C.
hasEponymReligion
Indicates that a religion is named after or derived from the name of a particular person.
-
D.
religiousName
Indicates that an entity has or is known by a name specifically associated with a religious role, identity, or context.
-
E.
titleHolderReligion
Indicates the religious affiliation associated with the holder of a particular title.
- 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_69ef9b6f8078819098b741274cd1a2ee |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6b342499c8190b85009a3f0f179e4 |
completed | May 3, 2026, 2:30 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b2a31e008190aacef03c2ebe5787 |
completed | May 3, 2026, 2:27 a.m. |
Created at: April 27, 2026, 8:47 p.m.