Triple
T10829695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W1 postcode district |
E255584
|
entity |
| Predicate | containsNeighbourhood |
P4813
|
FINISHED |
| Object | Mayfair |
E11937
|
NE 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: Mayfair | Statement: [W1 postcode district, containsNeighbourhood, Mayfair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayfair Context triple: [W1 postcode district, containsNeighbourhood, Mayfair]
-
A.
Mayfair
Mayfair is a residential neighborhood located within the city of Homewood, Alabama.
-
B.
Knightsbridge
Knightsbridge is an affluent central London district renowned for its luxury shopping, upscale residences, and proximity to Hyde Park.
-
C.
Mayfair neighborhood
The Mayfair neighborhood is a predominantly residential area in Northeast Philadelphia known for its rowhomes, strong community identity, and commercial corridor along Frankford Avenue.
-
D.
Belgravia
Belgravia is an affluent, predominantly residential district in central London known for its grand terraces, garden squares, and embassies.
-
E.
Mayfair, London, England
chosen
Mayfair, London, England is an affluent central London district known for its luxury residences, exclusive shops, and prestigious hotels and clubs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d74420fa188190b5b3c59e1a9f551d |
completed | April 9, 2026, 6:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de85a068b08190948c3ca32cdda147 |
completed | April 14, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:19 p.m.