Triple
T38701965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panay, Capiz |
E950162
|
entity |
| Predicate | bellLocation |
P191550
|
FINISHED |
| Object | belfry of Santa Monica Church |
—
|
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: belfry of Santa Monica Church | Statement: [Panay, Capiz, bellLocation, belfry of Santa Monica Church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bellLocation Context triple: [Panay, Capiz, bellLocation, belfry of Santa Monica Church]
-
A.
ringLocation
Indicates the spatial position or placement of a ring relative to a reference object or context.
-
B.
bellFoundry
Indicates that an entity operates as a foundry where bells are manufactured or cast.
-
C.
bellOrientation
Indicates the spatial direction or alignment in which a bell is positioned or facing.
-
D.
hasBellTowerLocation
Indicates the specific location where a bell tower is situated or attached relative to another structure or place.
-
E.
bellMounting
Indicates that one entity is mounted, fixed, or installed as a bell onto another supporting structure or surface.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:33 p.m.