Triple
T13248515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ladywell |
E315466
|
entity |
| Predicate | localAuthorityWard |
P61409
|
FINISHED |
| Object |
Ladywell ward
Ladywell ward is an electoral division in the London Borough of Lewisham, used for local government representation and administration.
|
E1029787
|
NE FINISHED |
How this triple was built (4 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: Ladywell ward | Statement: [Ladywell, localAuthorityWard, Ladywell ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ladywell ward Context triple: [Ladywell, localAuthorityWard, Ladywell ward]
-
A.
Ladywood ward
Ladywood ward is an electoral district within the city of Birmingham, England, represented on the local council and encompassing part of the central urban area.
-
B.
Aston ward
Aston ward is an electoral division within the Birmingham Ladywood constituency in Birmingham, England.
-
C.
Dunvant ward
Dunvant ward is an electoral division and suburban area within the City and County of Swansea in south Wales.
-
D.
Townhill ward
Townhill ward is an electoral division and residential area within the city and county of Swansea in South Wales.
-
E.
Bloomsbury ward
Bloomsbury ward is an electoral ward in the London Borough of Camden, covering much of the historic Bloomsbury area known for its universities, cultural institutions, and literary heritage.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ladywell ward Triple: [Ladywell, localAuthorityWard, Ladywell ward]
Generated description
Ladywell ward is an electoral division in the London Borough of Lewisham, used for local government representation and administration.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ladywell ward Target entity description: Ladywell ward is an electoral division in the London Borough of Lewisham, used for local government representation and administration.
-
A.
Ladywood ward
Ladywood ward is an electoral district within the city of Birmingham, England, represented on the local council and encompassing part of the central urban area.
-
B.
Aston ward
Aston ward is an electoral division within the Birmingham Ladywood constituency in Birmingham, England.
-
C.
Dunvant ward
Dunvant ward is an electoral division and suburban area within the City and County of Swansea in south Wales.
-
D.
Townhill ward
Townhill ward is an electoral division and residential area within the city and county of Swansea in South Wales.
-
E.
Bloomsbury ward
Bloomsbury ward is an electoral ward in the London Borough of Camden, covering much of the historic Bloomsbury area known for its universities, cultural institutions, and literary heritage.
- F. None of above. chosen
Provenance (5 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d9e7ea881908abc4b3a54896692 |
completed | April 10, 2026, 11:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff37f7448190b9c555cae010d3b6 |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f70476310c8190b13dc948c1f1ce95 |
completed | May 3, 2026, 8:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70578047c819089fc3044eceb4eac |
completed | May 3, 2026, 8:21 a.m. |
Created at: April 9, 2026, 9:24 p.m.