Triple
T6395561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C-3 |
E143931
|
entity |
| Predicate | majorStation |
P1071
|
FINISHED |
| Object | Getafe Industrial |
E92560
|
NE FINISHED |
How this triple was built (2 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: Getafe Industrial | Statement: [C-3, majorStation, Getafe Industrial]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Getafe Industrial Context triple: [C-3, majorStation, Getafe Industrial]
-
A.
Getafe
chosen
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.
-
B.
Alcorcón
Alcorcón is a suburban city in central Spain that forms part of the metropolitan area of Madrid.
-
C.
Leganés
Leganés is a major suburban city in central Spain, located just southwest of Madrid and known for its residential character, industry, and football club CD Leganés.
-
D.
Torrejón de Ardoz
Torrejón de Ardoz is a Spanish city in the eastern part of the Community of Madrid, known for its major air base and growing residential and industrial areas.
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0688275d0819086b58123c743a6db |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c63897a5408190b6aada0e5c67fe27 |
completed | March 27, 2026, 7:58 a.m. |
Created at: March 22, 2026, 4:35 p.m.