Triple
T4718908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallespir |
E104714
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Ripollès
Ripollès is a mountainous comarca in the Catalan Pyrenees of northeastern Spain, known for its Romanesque heritage, natural landscapes, and proximity to the French border.
|
E465704
|
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: Ripollès | Statement: [Vallespir, borders, Ripollès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ripollès Context triple: [Vallespir, borders, Ripollès]
-
A.
Ripoll
Ripoll is a Spanish surname of Catalan origin, notably borne by Colombian singer Shakira.
-
B.
Gandria
Gandria is a picturesque lakeside village in southern Switzerland known for its historic stone houses, narrow alleyways, and scenic setting on the shores of Lake Lugano.
-
C.
Gandesa
Gandesa is a historic town in Catalonia, Spain, known for its wine production and role in the Battle of the Ebro during the Spanish Civil War.
-
D.
Trambesòs
Trambesòs is a modern tram network serving Barcelona’s northeastern metropolitan area, connecting the city with nearby coastal and suburban districts.
-
E.
Gironella
Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
- 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: Ripollès Triple: [Vallespir, borders, Ripollès]
Generated description
Ripollès is a mountainous comarca in the Catalan Pyrenees of northeastern Spain, known for its Romanesque heritage, natural landscapes, and proximity to the French border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ripollès Target entity description: Ripollès is a mountainous comarca in the Catalan Pyrenees of northeastern Spain, known for its Romanesque heritage, natural landscapes, and proximity to the French border.
-
A.
Ripoll
Ripoll is a Spanish surname of Catalan origin, notably borne by Colombian singer Shakira.
-
B.
Gandria
Gandria is a picturesque lakeside village in southern Switzerland known for its historic stone houses, narrow alleyways, and scenic setting on the shores of Lake Lugano.
-
C.
Gandesa
Gandesa is a historic town in Catalonia, Spain, known for its wine production and role in the Battle of the Ebro during the Spanish Civil War.
-
D.
Trambesòs
Trambesòs is a modern tram network serving Barcelona’s northeastern metropolitan area, connecting the city with nearby coastal and suburban districts.
-
E.
Gironella
Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd642779a08190b01e588d515cf498 |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be108bc0048190aeea8674f75105e5 |
completed | March 21, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69be2e247f28819099e14db2c551a8f2 |
completed | March 21, 2026, 5:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be2ee962f88190927ccb32acdcc2e8 |
completed | March 21, 2026, 5:38 a.m. |
Created at: March 20, 2026, 1:18 p.m.