Triple
T11403408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaça de Ramon Berenguer el Gran |
E270172
|
entity |
| Predicate | hasBenchOrSeating |
P2608
|
FINISHED |
| Object | stone seating areas |
—
|
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: stone seating areas | Statement: [Plaça de Ramon Berenguer el Gran, hasBenchOrSeating, stone seating areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBenchOrSeating Context triple: [Plaça de Ramon Berenguer el Gran, hasBenchOrSeating, stone seating areas]
-
A.
hasShelteredSeating
Indicates that an entity provides seating that is protected from weather or other external elements.
-
B.
hasGrassSeatingArea
Indicates that an entity includes or provides a seating area located on a grass surface.
-
C.
hasBench
Indicates that one entity possesses, contains, or is equipped with a bench.
-
D.
outdoorSeating
Indicates that an establishment provides seating arrangements located outside the main indoor area.
-
E.
hasSeating
chosen
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014ab46881909fa1d425926c617b |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.