Triple
T5638840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | campanario (bell wall) |
E124214
|
entity |
| Predicate | bellOperation |
P65353
|
FINISHED |
| Object | rung by ropes |
—
|
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: rung by ropes | Statement: [campanario (bell wall), bellOperation, rung by ropes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bellOperation Context triple: [campanario (bell wall), bellOperation, rung by ropes]
-
A.
bellPattern
Indicates that one entity exhibits or follows a bell-shaped or bell-like pattern in relation to another entity or variable.
-
B.
numberOfBells
Indicates the quantity of bells associated with or present in a given entity or context.
-
C.
bellFoundry
Indicates that an entity operates as a foundry where bells are manufactured or cast.
-
D.
operateIn
Indicates that an entity performs its activities, functions, or services within a specified location, context, or domain.
-
E.
bellTowerStyle
Indicates the architectural style or design type of a bell tower in relation to a building or structure.
- 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_69c00824643c81909ffdb888a2d35189 |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c02283bb248190b29ac6255c78c5ec |
completed | March 22, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69c01b2168508190b64b355cf50034ad |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0727bc8190b16e9a669c04b4dd |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:41 p.m.