Triple
T31506654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amersham Museum |
E803833
|
entity |
| Predicate | hasNeighbourhoodContext |
P198652
|
FINISHED |
| Object | Chilterns area |
—
|
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: Chilterns area | Statement: [Amersham Museum, hasNeighbourhoodContext, Chilterns area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbourhoodContext Context triple: [Amersham Museum, hasNeighbourhoodContext, Chilterns area]
-
A.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
B.
hasNeighbourhoodCount
Indicates the number of neighbourhoods associated with a given entity.
-
C.
hasNeighbourhoodStatus
Indicates that an entity has a particular status, classification, or condition specifically in relation to a given neighbourhood.
-
D.
hasNeighborhoodBase
Indicates that one topological space has a specified collection of neighborhoods at each point that forms a neighborhood base for its topology.
-
E.
hasNeighbouringContext
Indicates that one context is directly adjacent to or closely related to another context in space, time, or structure.
- F. None of above. chosen
Provenance (4 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
| PDg | Predicate description generation | batch_69fefa05757481908fa38f5c604afbbe |
completed | May 9, 2026, 9:10 a.m. |
Created at: April 30, 2026, 9:47 p.m.