Triple
T14412401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Movida Madrileña |
E357361
|
entity |
| Predicate | mainLocation |
P3231
|
FINISHED |
| Object | Malasaña |
E591455
|
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: Malasaña | Statement: [Movida Madrileña, mainLocation, Malasaña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malasaña Context triple: [Movida Madrileña, mainLocation, Malasaña]
-
A.
Malasaña
chosen
Malasaña is a vibrant central Madrid neighborhood known for its bohemian atmosphere, nightlife, and alternative cultural scene.
-
B.
Los Molinos
Los Molinos is a small unincorporated rural community in Northern California known for its agricultural surroundings and location in Tehama County.
-
C.
Mataro
Mataro is an alternative name for Mourvèdre, a dark-skinned wine grape variety known for producing robust, tannic red wines often used in Mediterranean and Rhône-style blends.
-
D.
Barajas
Barajas is a Madrid Metro station on Line 8 that serves the Barajas district near Madrid–Barajas Airport.
-
E.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd55269d8c81909592277741a93db6 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.