Triple
T5932880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mappila Muslims |
E131976
|
entity |
| Predicate | notableMosqueArchitectureStyle |
P66993
|
FINISHED |
| Object | Kerala mosque architecture |
—
|
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: Kerala mosque architecture | Statement: [Mappila Muslims, notableMosqueArchitectureStyle, Kerala mosque architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableMosqueArchitectureStyle Context triple: [Mappila Muslims, notableMosqueArchitectureStyle, Kerala mosque architecture]
-
A.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
B.
JumaMosqueInstanceOf
Indicates that something is classified as an instance of a Juma (Friday) mosque.
-
C.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
-
D.
ShahJahanMosqueKnownFor
Indicates that something is notable or distinguished for its association with the Shah Jahan Mosque.
-
E.
isOneOfTheLargestMosquesIn
Indicates that the subject mosque ranks among the largest mosques located in the specified place or region.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03f23dd20819089dbf0de0d913602 |
completed | March 22, 2026, 7:12 p.m. |
Created at: March 22, 2026, 4 p.m.