Triple
T137950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Dudley Warner |
E2789
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object |
Dudley
Dudley is a masculine given name of English origin that has been borne by various notable figures in literature, politics, and entertainment.
|
E21380
|
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: Dudley | Statement: [Charles Dudley Warner, middleName, Dudley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dudley Context triple: [Charles Dudley Warner, middleName, Dudley]
-
A.
Blackley
Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
-
B.
Kendal Green
Kendal Green is a commuter rail station in Weston, Massachusetts, served by the MBTA's Fitchburg Line.
-
C.
Leigh
Leigh is a given name and surname of English origin, used for all genders and often considered a variant spelling of "Lee."
-
D.
Leatherhead
Leatherhead is a historic market town in the county of Surrey in South East England, situated on the River Mole and serving as a local commercial and commuter hub.
-
E.
Coventry
Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
- 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: Dudley Triple: [Charles Dudley Warner, middleName, Dudley]
Generated description
Dudley is a masculine given name of English origin that has been borne by various notable figures in literature, politics, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dudley Target entity description: Dudley is a masculine given name of English origin that has been borne by various notable figures in literature, politics, and entertainment.
-
A.
Blackley
Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
-
B.
Kendal Green
Kendal Green is a commuter rail station in Weston, Massachusetts, served by the MBTA's Fitchburg Line.
-
C.
Leigh
Leigh is a given name and surname of English origin, used for all genders and often considered a variant spelling of "Lee."
-
D.
Leatherhead
Leatherhead is a historic market town in the county of Surrey in South East England, situated on the River Mole and serving as a local commercial and commuter hub.
-
E.
Coventry
Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a6cab88190944c8f74d8d1605c |
completed | Feb. 28, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2e3bd8ee88190a708c0aa20b3c7d7 |
completed | Feb. 28, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_69a2e4a237e88190bc4393c308c315b5 |
completed | Feb. 28, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2e51d4394819099303040d072b165 |
completed | Feb. 28, 2026, 12:52 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.