Triple
T27844490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syon Lane area |
E703777
|
entity |
| Predicate | hasNearbyEmploymentArea |
P71206
|
FINISHED |
| Object | Great West Road Golden Mile |
—
|
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: Great West Road Golden Mile | Statement: [Syon Lane area, hasNearbyEmploymentArea, Great West Road Golden Mile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEmploymentArea Context triple: [Syon Lane area, hasNearbyEmploymentArea, Great West Road Golden Mile]
-
A.
hasNearbyEmploymentType
Indicates that one entity has an associated type of employment opportunity located in close physical proximity to another entity.
-
B.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
C.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
D.
nearbyEconomicActivity
chosen
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
E.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 27, 2026, 6:06 p.m.