Triple
T7643410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Woolverton |
E173063
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Woolverton
Woolverton is a surname most notably associated with American screenwriter and playwright Linda Woolverton, known for her work on major Disney films.
|
E677868
|
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: Woolverton | Statement: [Linda Woolverton, familyName, Woolverton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woolverton Context triple: [Linda Woolverton, familyName, Woolverton]
-
A.
Wolverton
Wolverton is a historic railway town in Buckinghamshire, England, now part of the Milton Keynes urban area.
-
B.
Wolterton
Wolterton is an English country estate and civil parish in Norfolk, best known as the setting of the historic Wolterton Hall.
-
C.
Woolverstone
Woolverstone is a small village and civil parish in Suffolk, England, situated on the banks of the River Orwell and known for its rural character and historic Woolverstone Hall.
-
D.
Woolston
Woolston is a district of Southampton in Hampshire, England, historically known for its shipbuilding and marine engineering industries.
-
E.
Wretton
Wretton is a small village and civil parish in Norfolk, England, situated in a rural area of the county.
- 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: Woolverton Triple: [Linda Woolverton, familyName, Woolverton]
Generated description
Woolverton is a surname most notably associated with American screenwriter and playwright Linda Woolverton, known for her work on major Disney films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Woolverton Target entity description: Woolverton is a surname most notably associated with American screenwriter and playwright Linda Woolverton, known for her work on major Disney films.
-
A.
Wolverton
Wolverton is a historic railway town in Buckinghamshire, England, now part of the Milton Keynes urban area.
-
B.
Wolterton
Wolterton is an English country estate and civil parish in Norfolk, best known as the setting of the historic Wolterton Hall.
-
C.
Woolverstone
Woolverstone is a small village and civil parish in Suffolk, England, situated on the banks of the River Orwell and known for its rural character and historic Woolverstone Hall.
-
D.
Woolston
Woolston is a district of Southampton in Hampshire, England, historically known for its shipbuilding and marine engineering industries.
-
E.
Wretton
Wretton is a small village and civil parish in Norfolk, England, situated in a rural area of the county.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faef96908190a7724b204f9d8c9e |
completed | March 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870d510f08190ad7706f582e8c1a0 |
completed | March 29, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69c87328c2cc81908b9fb89f5fee062e |
completed | March 29, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c873846a188190a3a1cc56ac247fb0 |
completed | March 29, 2026, 12:34 a.m. |
Created at: March 27, 2026, 3:58 p.m.