Triple
T21831503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamberí |
E539005
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object | Almagro |
—
|
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: Almagro | Statement: [Chamberí, hasNeighborhood, Almagro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Almagro Context triple: [Chamberí, hasNeighborhood, Almagro]
-
A.
Almagro
chosen
Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
-
B.
Almagro
Almagro is a traditional middle-class neighborhood in central Buenos Aires, Argentina, known for its historic tango culture, cafes, and densely populated residential streets.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Moncalvo
Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
-
E.
Alvear
Alvear is a town in the Rosario Department of Santa Fe Province, Argentina, functioning as part of the greater Rosario metropolitan area.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f091362d9081909f00ad7a2806d5cb |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 16, 2026, 6:55 p.m.