Triple
T26154565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayuntamiento de Chapala |
E659920
|
entity |
| Predicate | hasOfficialBuildingType |
P1844
|
FINISHED |
| Object | palacio municipal |
—
|
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: palacio municipal | Statement: [Ayuntamiento de Chapala, hasOfficialBuildingType, palacio municipal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialBuildingType Context triple: [Ayuntamiento de Chapala, hasOfficialBuildingType, palacio municipal]
-
A.
containsBuildingType
Indicates that a location or area includes at least one building of the specified type.
-
B.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
-
C.
buildingType
chosen
Indicates the specific category or function that characterizes what kind of building something is.
-
D.
hasBuildingClass
Indicates that a building is categorized as belonging to a specific building class or type.
-
E.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 26, 2026, 8:27 p.m.