Triple
T8223822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Retiro station |
E192128
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Retiro district |
E419021
|
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: Retiro district | Statement: [Retiro station, serves, Retiro district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Retiro district Context triple: [Retiro station, serves, Retiro district]
-
A.
Retiro district
chosen
Retiro district is a central district of Madrid, Spain, known for encompassing the famous El Retiro Park and several historic neighborhoods.
-
B.
Belén district
Belén district is a riverside neighborhood in Iquitos, Peru, known for its stilt houses, floating structures, and bustling traditional market.
-
C.
San Blas-Canillejas district
The San Blas-Canillejas district is a largely residential area in the eastern part of Madrid, Spain, known for its mix of post-war neighborhoods, green spaces, and major transport links.
-
D.
Malasaña area
Malasaña area is a central Madrid neighborhood known for its vibrant nightlife, alternative culture, and historic role in the Movida Madrileña countercultural movement.
-
E.
Luz district
Luz district is a historic central neighborhood in São Paulo, Brazil, known for its major cultural institutions, transport hub, and architectural landmarks.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77cc351481908d7dcd6d3d15d59f |
completed | March 31, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccee0fd9d0819094350c9c7887cabe |
completed | April 1, 2026, 10:06 a.m. |
Created at: March 30, 2026, 5:45 p.m.