Triple
T19678545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grosvenor Chapel |
E472519
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Mayfair |
—
|
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: Mayfair | Statement: [Grosvenor Chapel, location, Mayfair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayfair Context triple: [Grosvenor Chapel, location, Mayfair]
-
A.
Mayfair
Mayfair is a residential neighborhood on Chicago’s Northwest Side known for its diverse community and proximity to major parks and transit routes.
-
B.
Mayfair
Mayfair is a residential neighborhood in Northeast Washington, D.C., known for its proximity to the Anacostia River and its mix of rowhouses and apartment complexes.
-
C.
Mayfair
Mayfair is a residential neighborhood located within the city of Homewood, Alabama.
-
D.
Mayfair
chosen
Mayfair is an affluent central London district known for its luxury shops, exclusive residences, and prestigious hotels and restaurants.
-
E.
Knightsbridge
Knightsbridge is an affluent central London district renowned for its luxury shopping, upscale residences, and proximity to Hyde Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e641bda8348190b0c7816c50aca923 |
completed | April 20, 2026, 3:09 p.m. |
Created at: April 10, 2026, 1:45 p.m.