Triple
T6027993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Walker |
E134227
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Swoyer
Swoyer is a surname associated with individuals such as Nancy Walker.
|
E564439
|
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: Swoyer | Statement: [Nancy Walker, familyName, Swoyer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swoyer Context triple: [Nancy Walker, familyName, Swoyer]
-
A.
Sawyer
Sawyer is a surname of English origin commonly borne by individuals in English-speaking countries.
-
B.
Jory
Jory is a fictional character appearing in Émile Zola’s novel "L’Œuvre," part of his Rougon-Macquart series exploring art, ambition, and society in 19th-century France.
-
C.
Topher Brink
Topher Brink is a brilliant but morally conflicted programmer and neuroscientist in the TV series "Dollhouse," responsible for designing and overseeing the mind-wiping and imprinting technology used on the show's "dolls."
-
D.
Dylan Piper
Dylan Piper is a cautious, bookish member of the Cromwell family in the Disney Channel "Halloweentown" film series, known for gradually embracing his magical heritage.
-
E.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
- 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: Swoyer Triple: [Nancy Walker, familyName, Swoyer]
Generated description
Swoyer is a surname associated with individuals such as Nancy Walker.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Swoyer Target entity description: Swoyer is a surname associated with individuals such as Nancy Walker.
-
A.
Sawyer
Sawyer is a surname of English origin commonly borne by individuals in English-speaking countries.
-
B.
Jory
Jory is a fictional character appearing in Émile Zola’s novel "L’Œuvre," part of his Rougon-Macquart series exploring art, ambition, and society in 19th-century France.
-
C.
Topher Brink
Topher Brink is a brilliant but morally conflicted programmer and neuroscientist in the TV series "Dollhouse," responsible for designing and overseeing the mind-wiping and imprinting technology used on the show's "dolls."
-
D.
Dylan Piper
Dylan Piper is a cautious, bookish member of the Cromwell family in the Disney Channel "Halloweentown" film series, known for gradually embracing his magical heritage.
-
E.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560e3c2c8190aea2619386fc5538 |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1137d6a648190a91795fb679a891c |
completed | March 23, 2026, 10:18 a.m. |
| NEDg | Description generation | batch_69c11423d05c81909298ae598c80ccb0 |
completed | March 23, 2026, 10:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11498f2948190bcca6b8054186e75 |
completed | March 23, 2026, 10:23 a.m. |
Created at: March 22, 2026, 4:07 p.m.