Triple
T24042566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle de Gerona (Madrid) |
E595423
|
entity |
| Predicate | belongsToHistoricArea |
P133942
|
FINISHED |
| Object | Madrid de los Austrias |
—
|
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: Madrid de los Austrias | Statement: [Calle de Gerona (Madrid), belongsToHistoricArea, Madrid de los Austrias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToHistoricArea Context triple: [Calle de Gerona (Madrid), belongsToHistoricArea, Madrid de los Austrias]
-
A.
hasHistoricDistrictAssociation
Indicates a relationship in which an entity is associated with, linked to, or part of a designated historic district.
-
B.
partOfHistoricalArea
chosen
Indicates that one entity is located within or belongs to a designated historical area or heritage zone.
-
C.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
D.
historicAreaIncludes
Indicates that a designated historic area geographically contains or encompasses another place or feature within its boundaries.
-
E.
hasHistoricDistrict
Indicates that an entity possesses or contains a designated historic district within its boundaries or domain.
- F. None of above.
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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8db3b4c81908a36eace8ec136cc |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:58 p.m.