Triple
T17797534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Javier Prado |
E444331
|
entity |
| Predicate | passesThroughDistrict |
P45427
|
FINISHED |
| Object | La Molina |
—
|
NE NERFINISHED |
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: La Molina | Statement: [Avenida Javier Prado, passesThroughDistrict, La Molina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Molina Context triple: [Avenida Javier Prado, passesThroughDistrict, La Molina]
-
A.
La Molina
chosen
La Molina is an affluent residential and educational district located in the eastern part of Lima, Peru.
-
B.
De Molina
De Molina is a variant form of the surname Molina, commonly found in Spanish-speaking regions.
-
C.
El Molinón
El Molinón is a historic football stadium in Gijón, Spain, best known as the longtime home ground of Sporting de Gijón and one of the oldest professional football venues in the country.
-
D.
Pinar de Chamartín
Pinar de Chamartín is a major Madrid Metro interchange station in the north of the city that serves as a key terminal and transfer hub for multiple lines.
-
E.
Torreblanca
Torreblanca is a coastal resort town on Spain’s Costa del Azahar, known for its Mediterranean beaches and tourism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487fbc83481909a30fc7203b64099 |
completed | April 19, 2026, 7:44 a.m. |
Created at: April 10, 2026, 10:13 a.m.