Triple
T590783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Church Unitarian Littleton |
E17263
|
entity |
| Predicate | hasPhysicalStructureType |
P841
|
FINISHED |
| Object | church 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: church building | Statement: [First Church Unitarian Littleton, hasPhysicalStructureType, church building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalStructureType Context triple: [First Church Unitarian Littleton, hasPhysicalStructureType, church building]
-
A.
hasStructureType
chosen
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
B.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
C.
hasInfrastructureType
Indicates that an entity possesses or is associated with a specific category or type of infrastructure.
-
D.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
E.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bb8ff0081909cd53d88930e2693 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.