Triple
T6350056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza Mayor de Tordesillas |
E142845
|
entity |
| Predicate | hasSurroundingBuildingUse |
P13155
|
FINISHED |
| Object | municipal services |
—
|
LITERAL 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: municipal services | Statement: [Plaza Mayor de Tordesillas, hasSurroundingBuildingUse, municipal services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundingBuildingUse Context triple: [Plaza Mayor de Tordesillas, hasSurroundingBuildingUse, municipal services]
-
A.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
B.
hasBuildingStyleInSurroundings
Indicates that an entity is surrounded by or located in an area characterized by a particular building style.
-
C.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
D.
hasSurroundings
chosen
Indicates that an entity is located within or encircled by a particular environment, context, or set of surrounding elements.
-
E.
hasMainBuildingNear
Indicates that the primary or central building associated with an entity is located in close physical proximity to another specified entity or place.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067bcec2c8190bb383605847b0f0b |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.