Triple
T10733267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canóvanas barrio-pueblo |
E253126
|
entity |
| Predicate | hasCivicBuildings |
P14728
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Canóvanas barrio-pueblo, hasCivicBuildings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivicBuildings Context triple: [Canóvanas barrio-pueblo, hasCivicBuildings, yes]
-
A.
hasNearbyCivicBuilding
Indicates that one entity is located close to, or in the immediate vicinity of, a civic building such as a government, public service, or community facility.
-
B.
hasNearbyCulturalBuilding
Indicates that one entity is located close to another entity that is a cultural building, such as a museum, theater, or gallery.
-
C.
hasTerminalBuildings
Indicates that one entity possesses or includes terminal buildings associated with it.
-
D.
containsBuilding
chosen
Indicates that one location or area includes a building within its boundaries.
-
E.
hasClericalStructure
Indicates that an entity possesses an organized clerical or administrative hierarchy or framework.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7101ff9808190a27fcc06da097ea3 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.