Triple
T2965299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Girona |
E80146
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Call de Girona
Call de Girona is the historic Jewish quarter of Girona, Spain, known for its well-preserved medieval streets and significant Jewish heritage.
|
E315243
|
NE FINISHED |
How this triple was built (4 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: Call de Girona | Statement: [Girona, hasPart, Call de Girona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Call de Girona Context triple: [Girona, hasPart, Call de Girona]
-
A.
Girona FC
Girona FC is a Spanish professional football club based in Girona, Catalonia, that competes in La Liga.
-
B.
Melgar
Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
-
C.
Vélez
Vélez is a municipality in Colombia’s Santander Department known for its colonial heritage and traditional sweets.
-
D.
Vélez
Vélez is a Spanish-language surname common in Latin America and Spain, borne by various notable figures in arts, sports, and public life.
-
E.
Sporting de Gijón
Sporting de Gijón is a Spanish professional football club based in Gijón, Asturias, known for its long history in La Liga and strong local fan base.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Call de Girona Triple: [Girona, hasPart, Call de Girona]
Generated description
Call de Girona is the historic Jewish quarter of Girona, Spain, known for its well-preserved medieval streets and significant Jewish heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Call de Girona Target entity description: Call de Girona is the historic Jewish quarter of Girona, Spain, known for its well-preserved medieval streets and significant Jewish heritage.
-
A.
Girona FC
Girona FC is a Spanish professional football club based in Girona, Catalonia, that competes in La Liga.
-
B.
Melgar
Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
-
C.
Vélez
Vélez is a municipality in Colombia’s Santander Department known for its colonial heritage and traditional sweets.
-
D.
Vélez
Vélez is a Spanish-language surname common in Latin America and Spain, borne by various notable figures in arts, sports, and public life.
-
E.
Sporting de Gijón
Sporting de Gijón is a Spanish professional football club based in Gijón, Asturias, known for its long history in La Liga and strong local fan base.
- F. None of above. chosen
Provenance (5 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad995a28e88190a4d6b9ef2c0d8e61 |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc9bc190819087cb35ee7c78825a |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b0fd25e07c819088b2b1bcef4cf54e |
completed | March 11, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b100ecbee081908832ddec0efdc751 |
completed | March 11, 2026, 5:43 a.m. |
Created at: March 8, 2026, 2:58 p.m.