Triple
T16733075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Wickersham |
E406641
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wickersham
Wickersham is an English-origin surname borne by various notable individuals in politics, law, and public service.
|
E1230351
|
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: Wickersham | Statement: [Victor Wickersham, familyName, Wickersham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wickersham Context triple: [Victor Wickersham, familyName, Wickersham]
-
A.
Shaughnessy
Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
-
B.
Harlan Rook
Harlan Rook is the psychopathic, fame-obsessed serial killer and main antagonist in the 1988 Dirty Harry film "The Dead Pool."
-
C.
Wilbur Fisk
Wilbur Fisk was a prominent 19th-century American Methodist minister and educator who served as the first president of Wesleyan University in Middletown, Connecticut.
-
D.
Whitman Chambers
Whitman Chambers was an American screenwriter known for his work on mid-20th-century crime and mystery films.
-
E.
Erastus Milo Fisk
Erastus Milo Fisk was a 19th-century American politician and public figure, best known for his involvement in regional civic and governmental affairs.
- 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: Wickersham Triple: [Victor Wickersham, familyName, Wickersham]
Generated description
Wickersham is an English-origin surname borne by various notable individuals in politics, law, and public service.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wickersham Target entity description: Wickersham is an English-origin surname borne by various notable individuals in politics, law, and public service.
-
A.
Shaughnessy
Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
-
B.
Harlan Rook
Harlan Rook is the psychopathic, fame-obsessed serial killer and main antagonist in the 1988 Dirty Harry film "The Dead Pool."
-
C.
Wilbur Fisk
Wilbur Fisk was a prominent 19th-century American Methodist minister and educator who served as the first president of Wesleyan University in Middletown, Connecticut.
-
D.
Whitman Chambers
Whitman Chambers was an American screenwriter known for his work on mid-20th-century crime and mystery films.
-
E.
Erastus Milo Fisk
Erastus Milo Fisk was a 19th-century American politician and public figure, best known for his involvement in regional civic and governmental affairs.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3748d08190a57ae40f54aa63c4 |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d4c723c8190ad92628f4164d11c |
completed | May 10, 2026, 2:59 p.m. |
| NEDg | Description generation | batch_6a009e08b56c8190833d5f64945a979b |
completed | May 10, 2026, 3:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a009eb209cc819081c5fb2c89583602 |
completed | May 10, 2026, 3:05 p.m. |
Created at: April 10, 2026, 5:20 a.m.