Triple
T24294771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qibla (toward the Kaaba) |
E605927
|
entity |
| Predicate | associatedWithMosque |
P155427
|
FINISHED |
| Object | Masjid al-Haram |
—
|
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: Masjid al-Haram | Statement: [Qibla (toward the Kaaba), associatedWithMosque, Masjid al-Haram]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithMosque Context triple: [Qibla (toward the Kaaba), associatedWithMosque, Masjid al-Haram]
-
A.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
B.
hasTypeOfMosque
Indicates that an entity is classified as, or identified to be, a particular type or category of mosque.
-
C.
religiousAffiliationOfMosque
Indicates the religious denomination or sect with which a mosque is associated or to which it belongs.
-
D.
convertedToMosque
Indicates that a building or structure was changed in function or use to become a mosque.
-
E.
associatedWithAntiCaliph
Indicates a relationship in which an entity is connected or linked to an anti-caliph, typically through support, affiliation, or involvement.
- 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f291593c0881908a6827f0d8899fe6 |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:09 a.m.