Triple
T3842865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leganés |
E93493
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
CD Leganés
CD Leganés is a Spanish professional football club based in Leganés, Madrid, known for competing in La Liga and the Segunda División.
|
E392402
|
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: CD Leganés | Statement: [Leganés, knownFor, CD Leganés]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CD Leganés Context triple: [Leganés, knownFor, CD Leganés]
-
A.
CD Guadalajara
CD Guadalajara is a Spanish football club based in Guadalajara that competes in the country’s lower professional divisions.
-
B.
Les Corts
Les Corts is a district in the western part of Barcelona, Spain, known for its residential character and for hosting the FC Barcelona stadium, Camp Nou.
-
C.
Getafe
Getafe is a city in central Spain that forms part of the Madrid metropolitan area and is known for its industrial base, university campus, and air force history.
-
D.
Rayo Vallecano
Rayo Vallecano is a Spanish football club from the Madrid neighborhood of Vallecas, known for its working-class identity and passionate local support.
-
E.
Melgar
Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
- 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: CD Leganés Triple: [Leganés, knownFor, CD Leganés]
Generated description
CD Leganés is a Spanish professional football club based in Leganés, Madrid, known for competing in La Liga and the Segunda División.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CD Leganés Target entity description: CD Leganés is a Spanish professional football club based in Leganés, Madrid, known for competing in La Liga and the Segunda División.
-
A.
CD Guadalajara
CD Guadalajara is a Spanish football club based in Guadalajara that competes in the country’s lower professional divisions.
-
B.
Les Corts
Les Corts is a district in the western part of Barcelona, Spain, known for its residential character and for hosting the FC Barcelona stadium, Camp Nou.
-
C.
Getafe
Getafe is a city in central Spain that forms part of the Madrid metropolitan area and is known for its industrial base, university campus, and air force history.
-
D.
Rayo Vallecano
Rayo Vallecano is a Spanish football club from the Madrid neighborhood of Vallecas, known for its working-class identity and passionate local support.
-
E.
Melgar
Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb397ac81908f74a42a0eeb8682 |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5040f93948190b104cf1b7db671b7 |
completed | March 14, 2026, 6:45 a.m. |
| NEDg | Description generation | batch_69b504c46dcc8190a9775c39e5c734a9 |
completed | March 14, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b505742830819093a861bde17c03c0 |
completed | March 14, 2026, 6:51 a.m. |
Created at: March 9, 2026, 3:18 p.m.