Triple
T3293898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 road |
E69163
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Hammersmith |
E81474
|
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: Hammersmith | Statement: [A4 road, passesThrough, Hammersmith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hammersmith Context triple: [A4 road, passesThrough, Hammersmith]
-
A.
Hammersmith
chosen
Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
-
B.
Harlesden
Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
-
C.
Kensington and Chelsea
Kensington and Chelsea is a central-west London borough known for its affluent residential areas, cultural institutions, and landmarks such as Kensington Palace and the King's Road.
-
D.
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.
-
E.
Lambeth
Lambeth is a central London borough on the south bank of the River Thames, known for landmarks such as the London Eye and its diverse urban communities.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb074f35081909dd3c8a09544b5f1 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c1cbe848190a75c0e7108a5bc2c |
completed | March 14, 2026, 11:53 a.m. |
Created at: March 8, 2026, 3:10 p.m.