Triple
T34111429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nankana Sahib District |
E874847
|
entity |
| Predicate | majorReligionSiteFor |
P175289
|
FINISHED |
| Object | Sikhism |
—
|
NE NERFINISHED |
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: Sikhism | Statement: [Nankana Sahib District, majorReligionSiteFor, Sikhism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorReligionSiteFor Context triple: [Nankana Sahib District, majorReligionSiteFor, Sikhism]
-
A.
connectsReligiousSite
Indicates a relationship where something serves as a link, route, or association between one religious site and another.
-
B.
religiousAffiliationOfMajorSite
Indicates the religion or denomination with which a major site (such as a temple, church, mosque, or shrine) is formally associated.
-
C.
majorReligionCanBe
Indicates that an entity can have a particular major religion as one of its possible primary religious affiliations.
-
D.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
E.
traditionalReligionPlace
chosen
Indicates that a place is traditionally associated with the practice, worship, or activities of a particular religion.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:53 a.m.