Triple
T14443866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chelsea Thayer Wayne |
E358153
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Bill Ray
Bill Ray is the husband of Chelsea Thayer Wayne, known primarily in relation to her.
|
E1099503
|
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: Bill Ray | Statement: [Chelsea Thayer Wayne, spouse, Bill Ray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Ray Context triple: [Chelsea Thayer Wayne, spouse, Bill Ray]
-
A.
Pete Travis
Pete Travis is a British film and television director best known for his work on the 2012 science fiction action film "Dredd" and political thrillers such as "Vantage Point."
-
B.
Bobby Ellis
Bobby Ellis is a student associated with St. Clare's School.
-
C.
Dennis Crosby
Dennis Crosby was an American singer and actor best known as one of Bing Crosby’s sons who performed with his brothers as part of the Crosby family entertainment legacy.
-
D.
Ned Leeds
Ned Leeds is Peter Parker’s best friend and comic-relief sidekick in the Marvel Cinematic Universe, known for his enthusiastic support of Spider-Man and his humorous, nerdy personality.
-
E.
Bill Snibson
Bill Snibson is the boisterous, working-class Cockney hero of the musical "Me and My Girl," whose unexpected inheritance of an aristocratic title drives the show's central comedy and romance.
- 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: Bill Ray Triple: [Chelsea Thayer Wayne, spouse, Bill Ray]
Generated description
Bill Ray is the husband of Chelsea Thayer Wayne, known primarily in relation to her.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bill Ray Target entity description: Bill Ray is the husband of Chelsea Thayer Wayne, known primarily in relation to her.
-
A.
Pete Travis
Pete Travis is a British film and television director best known for his work on the 2012 science fiction action film "Dredd" and political thrillers such as "Vantage Point."
-
B.
Bobby Ellis
Bobby Ellis is a student associated with St. Clare's School.
-
C.
Dennis Crosby
Dennis Crosby was an American singer and actor best known as one of Bing Crosby’s sons who performed with his brothers as part of the Crosby family entertainment legacy.
-
D.
Ned Leeds
Ned Leeds is Peter Parker’s best friend and comic-relief sidekick in the Marvel Cinematic Universe, known for his enthusiastic support of Spider-Man and his humorous, nerdy personality.
-
E.
Bill Snibson
Bill Snibson is the boisterous, working-class Cockney hero of the musical "Me and My Girl," whose unexpected inheritance of an aristocratic title drives the show's central comedy and romance.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de915d28ec81909e72124e9dd67bfb |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bdd0f388190870ddd01f66d3e99 |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5e188a148190bb166b7d50ad3b46 |
completed | May 8, 2026, 3:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5ea592cc8190a47a2f6a511c0549 |
completed | May 8, 2026, 3:55 a.m. |
Created at: April 10, 2026, 1:19 a.m.