Triple
T4254600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valdemoro |
E95940
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Pinto |
E80243
|
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: Pinto | Statement: [Valdemoro, nearbyCity, Pinto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pinto Context triple: [Valdemoro, nearbyCity, Pinto]
-
A.
Pinto
chosen
Pinto is a municipality in the southern part of the Community of Madrid, Spain, known for its residential character and location near the region’s capital.
-
B.
Palomino
Palomino is a white grape variety from Spain that is most famously used to produce dry sherries, particularly in the Jerez region.
-
C.
Bassett
Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
-
D.
Angus
Angus is a historic county and region on the east coast of Scotland known for its rural landscapes, agriculture, and coastal towns.
-
E.
Merle
Merle is a given name most famously associated with American country music legend Merle Haggard.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ec036e8819087d8585170707545 |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a887703c81909a40f23f83154b8c |
completed | March 14, 2026, 6:27 p.m. |
Created at: March 12, 2026, 11:06 p.m.