Triple
T6684352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matadero Madrid |
E152063
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Arganzuela district |
E533339
|
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: Arganzuela district | Statement: [Matadero Madrid, locatedIn, Arganzuela district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arganzuela district Context triple: [Matadero Madrid, locatedIn, Arganzuela district]
-
A.
Arganzuela district
chosen
Arganzuela district is a central district of Madrid, Spain, known for its mix of residential neighborhoods, cultural venues, and proximity to the Manzanares River.
-
B.
Belén district
Belén district is a riverside neighborhood in Iquitos, Peru, known for its stilt houses, floating structures, and bustling traditional market.
-
C.
La Molina district
La Molina district is an affluent residential and educational district located in the eastern part of Lima, Peru.
-
D.
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.
-
E.
Al Olaya district
Al Olaya district is a prominent commercial and business area in central Riyadh, Saudi Arabia, known for its modern skyscrapers, shopping centers, and major 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b122df14819082068af37611b691 |
completed | March 27, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7ae8f388190a3c78c89b7293804 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:04 p.m.