Triple
T15350332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hundred of Salford |
E367033
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Blackley |
E17502
|
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: Blackley | Statement: [Hundred of Salford, contains, Blackley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blackley Context triple: [Hundred of Salford, contains, Blackley]
-
A.
Blackley
chosen
Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
-
B.
Banwell
Banwell is a village and civil parish in North Somerset, England, known for its historic caves and medieval architecture.
-
C.
Barrowfield
Barrowfield is a residential district in Glasgow, Scotland, known historically for its working-class community and proximity to major football and industrial sites in the city's East End.
-
D.
Broadley
Broadley is a locality or district that forms part of the town of Whitworth in England.
-
E.
Kearsley
Kearsley is a town in Greater Manchester, England, historically part of Lancashire and known for its industrial heritage.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e290efc8190b22c95dcd3e5f57f |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01fd53688190939787a3d6ff3bb9 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.