Triple
T15213227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chieveley |
E363569
|
entity |
| Predicate | hasServiceAreaNearby |
P5648
|
FINISHED |
| Object | Moto Chieveley services |
—
|
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: Moto Chieveley services | Statement: [Chieveley, hasServiceAreaNearby, Moto Chieveley services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceAreaNearby Context triple: [Chieveley, hasServiceAreaNearby, Moto Chieveley services]
-
A.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
C.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
D.
hasServiceAreas
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
-
E.
areaOfService
Indicates the geographic or functional region within which a service is provided or applicable.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076c9e2481909d7a464b2172f4bf |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.