Triple
T16156306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sloane Street |
E392051
|
entity |
| Predicate | terminusNorth |
P3375
|
FINISHED |
| Object | Knightsbridge |
E77845
|
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: Knightsbridge | Statement: [Sloane Street, terminusNorth, Knightsbridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knightsbridge Context triple: [Sloane Street, terminusNorth, Knightsbridge]
-
A.
Knightsbridge
chosen
Knightsbridge is an affluent central London district renowned for its luxury shopping, upscale residences, and proximity to Hyde Park.
-
B.
Sloane Square
Sloane Square is a prominent public square and transport hub in central London, known for its upscale shops, theatres, and proximity to the fashionable Chelsea district.
-
C.
Mayfair
Mayfair is a residential neighborhood located within the city of Homewood, Alabama.
-
D.
Mayfair
Mayfair is an affluent central London district known for its luxury shops, exclusive residences, and prestigious hotels and restaurants.
-
E.
St John’s Wood
St John’s Wood is an affluent residential district in northwest London, known for its tree-lined streets, elegant villas, and landmarks such as Lord’s Cricket Ground and Abbey Road.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5aa57c8190a9d89dd57e30318f |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007833960819088334e10258a9d72 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:01 a.m.