Triple
T12995400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catalan institutions |
E322018
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Girona |
E80146
|
NE 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: Girona | Statement: [Catalan institutions, location, Girona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Girona Context triple: [Catalan institutions, location, Girona]
-
A.
Girona
chosen
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
B.
Lleida
Lleida is a historic city in western Catalonia, Spain, known for its medieval Seu Vella cathedral and role as a regional agricultural and commercial center.
-
C.
Besalú
Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
-
D.
Tàrrega
Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
-
E.
Urgell
Urgell is a historical comarca in inland Catalonia, known for its agricultural landscapes, medieval towns, and role as part of the broader Urgell region that includes the famous bishopric and valley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7877f481908a03f1077600e58a |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef5a0824819097e41163e3092b68 |
completed | May 9, 2026, 8:24 a.m. |
Created at: April 9, 2026, 8:45 p.m.