Triple
T24539762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nayabad Mosque |
E607056
|
entity |
| Predicate | hasNiche |
P120197
|
FINISHED |
| Object | mihrab niche on qibla wall |
—
|
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: mihrab niche on qibla wall | Statement: [Nayabad Mosque, hasNiche, mihrab niche on qibla wall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNiche Context triple: [Nayabad Mosque, hasNiche, mihrab niche on qibla wall]
-
A.
hasNichesOn
chosen
Indicates that one entity possesses or contains specialized areas, sections, or recesses that are located on or within another entity.
-
B.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
D.
hasSpecialtyChannel
Indicates that one entity provides or is associated with a dedicated channel focused on a particular specialty or subject area for another entity.
-
E.
hasInterestType
Indicates that an entity is associated with a specific category or type of interest it holds or is concerned with.
- 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:26 a.m.