Triple
T9596093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Tomatina |
E231535
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Buñol
Buñol is a small town in Spain’s Valencia region best known for hosting the annual La Tomatina tomato-throwing festival.
|
E820512
|
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: Buñol | Statement: [La Tomatina, locatedIn, Buñol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buñol Context triple: [La Tomatina, locatedIn, Buñol]
-
A.
Esplugues de Llobregat
Esplugues de Llobregat is a municipality in the metropolitan area of Barcelona, Catalonia, known for its residential character and proximity to the Catalan capital.
-
B.
Mataró
Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
-
C.
Martorell
Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
-
D.
Igualada
Igualada is a historic town in Catalonia, Spain, known for its traditional textile and leather industries and its location near Barcelona.
-
E.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
- 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: Buñol Triple: [La Tomatina, locatedIn, Buñol]
Generated description
Buñol is a small town in Spain’s Valencia region best known for hosting the annual La Tomatina tomato-throwing festival.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Buñol Target entity description: Buñol is a small town in Spain’s Valencia region best known for hosting the annual La Tomatina tomato-throwing festival.
-
A.
Esplugues de Llobregat
Esplugues de Llobregat is a municipality in the metropolitan area of Barcelona, Catalonia, known for its residential character and proximity to the Catalan capital.
-
B.
Mataró
Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
-
C.
Martorell
Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
-
D.
Igualada
Igualada is a historic town in Catalonia, Spain, known for its traditional textile and leather industries and its location near Barcelona.
-
E.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a164c20819093fa863f8f5f79c0 |
completed | April 1, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcaf94608190992124965a805228 |
completed | April 5, 2026, 1:36 a.m. |
| NEDg | Description generation | batch_69d1bf70697081909daa19110c20969e |
completed | April 5, 2026, 1:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1bfd7e5c08190ae679641f5254dc7 |
completed | April 5, 2026, 1:50 a.m. |
Created at: March 30, 2026, 8:07 p.m.