Triple
T13683121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N-IV road |
E328050
|
entity |
| Predicate | passesNearCity |
P3945
|
FINISHED |
| Object | Getafe |
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 | Statement: [N-IV road, passesNearCity, Getafe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Getafe Context triple: [N-IV road, passesNearCity, Getafe]
-
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.
Getafe CF
Getafe CF is a Spanish professional football club based in the Madrid suburb of Getafe that competes in La Liga.
-
D.
Valmadrid
Valmadrid is a small municipality in the province of Zaragoza, Aragon, Spain, situated within the semi-arid landscapes characteristic of the Campo de Belchite region.
-
E.
Paterna
Paterna is a municipality in eastern Spain known for its proximity to the city of Valencia and its mix of industrial activity and residential areas.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc66e75188190a9e82fdc5eb26513 |
completed | April 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944551b481909833cdcff198889c |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.