Triple
T10741708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Works of Lluís Domènech i Montaner |
E253340
|
entity |
| Predicate | hasComponentUse |
P85175
|
FINISHED |
| Object | concert hall |
—
|
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: concert hall | Statement: [Works of Lluís Domènech i Montaner, hasComponentUse, concert hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComponentUse Context triple: [Works of Lluís Domènech i Montaner, hasComponentUse, concert hall]
-
A.
hasSubcomponent
Indicates that one entity is a constituent part or component of another, larger entity.
-
B.
hasUsePattern
Indicates a characteristic or recurring way in which something is typically used or applied.
-
C.
hasComponentProgram
Indicates that one program includes or is composed of another program as a component or sub-program.
-
D.
hasComponentCurrent
Indicates that an entity currently includes or contains a specific component as part of its present composition or structure.
-
E.
hasPartUsed
chosen
Indicates that an entity utilizes another entity as a component or constituent part in its structure, function, or operation.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710456ec88190ad8aff8804d13aa9 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.