Triple
T12970996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crail Harbour |
E321393
|
entity |
| Predicate | hasBuildingTypeNearby |
P50464
|
FINISHED |
| Object | fishermen's cottages |
—
|
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: fishermen's cottages | Statement: [Crail Harbour, hasBuildingTypeNearby, fishermen's cottages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingTypeNearby Context triple: [Crail Harbour, hasBuildingTypeNearby, fishermen's cottages]
-
A.
hasNeighboringBuilding
Indicates that one building is located adjacent to or directly next to another building.
-
B.
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.
-
C.
hasMainBuildingNear
Indicates that the primary or central building associated with an entity is located in close physical proximity to another specified entity or place.
-
D.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:35 p.m.