Triple
T32782722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairhaven Center Historic District |
E838399
|
entity |
| Predicate | containsTypeOfBuilding |
P50464
|
FINISHED |
| Object | civic building |
—
|
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: civic building | Statement: [Fairhaven Center Historic District, containsTypeOfBuilding, civic building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsTypeOfBuilding Context triple: [Fairhaven Center Historic District, containsTypeOfBuilding, civic building]
-
A.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified type.
-
B.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
C.
belongsToBuildingType
Indicates that something is classified as being of a particular building type.
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
intendedBuildingType
Indicates the type of building that something is planned or designed to be.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fff09dae088190bd8460060d778feb |
completed | May 10, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69fff0027c5c8190baa5c7a15852cbe0 |
completed | May 10, 2026, 2:40 a.m. |
Created at: May 1, 2026, 1:14 a.m.