Triple
T36717933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Number Three, Bagshot Row |
E906963
|
entity |
| Predicate | neighboringResidence |
P77342
|
FINISHED |
| Object | Number One, Bagshot Row |
—
|
NE NERFINISHED |
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: Number One, Bagshot Row | Statement: [Number Three, Bagshot Row, neighboringResidence, Number One, Bagshot Row]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighboringResidence Context triple: [Number Three, Bagshot Row, neighboringResidence, Number One, Bagshot Row]
-
A.
neighboringFamily
Indicates that one family lives next to or very close to another family, forming a direct neighborhood relationship.
-
B.
hasNeighbouringEstate
Indicates that one estate is directly adjacent to or shares a boundary with another estate.
-
C.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
D.
hasNeighboringBuilding
chosen
Indicates that one building is located adjacent to or directly next to another building.
-
E.
neighboringTo
Indicates that one entity is located directly adjacent or very close to another entity, sharing a common boundary or immediate vicinity.
- 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_69f76e73ad108190a5241585f2303e9a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:12 p.m.