Triple
T4235813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamiers |
E94688
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Tàrrega
Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
|
E427926
|
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: Tàrrega | Statement: [Pamiers, twinTown, Tàrrega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tàrrega Context triple: [Pamiers, twinTown, Tàrrega]
-
A.
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.
-
B.
Ripoll
Ripoll is a Spanish surname of Catalan origin, notably borne by Colombian singer Shakira.
-
C.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
D.
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.
-
E.
Reus
Reus is a city in Catalonia, Spain, known as the birthplace of architect Antoni Gaudí and for its historic center and vermouth production.
- 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: Tàrrega Triple: [Pamiers, twinTown, Tàrrega]
Generated description
Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tàrrega Target entity description: Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
-
A.
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.
-
B.
Ripoll
Ripoll is a Spanish surname of Catalan origin, notably borne by Colombian singer Shakira.
-
C.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
D.
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.
-
E.
Reus
Reus is a city in Catalonia, Spain, known as the birthplace of architect Antoni Gaudí and for its historic center and vermouth production.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e72ff588190a50c04ab975612dd |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b77632d08190ab7c12986e2cee61 |
completed | March 14, 2026, 7:31 p.m. |
| NEDg | Description generation | batch_69b5c24a46148190b0be076df2b9757a |
completed | March 14, 2026, 8:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c2d130188190acc9cfd5a64ab0ee |
completed | March 14, 2026, 8:19 p.m. |
Created at: March 12, 2026, 11:05 p.m.