Triple
T12138940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cobb |
E289132
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Lou Myers
Lou Myers was an American actor best known for his role as Mr. Vernon Gaines on the television series "A Different World."
|
E968226
|
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: Lou Myers | Statement: [Cobb, castMember, Lou Myers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lou Myers Context triple: [Cobb, castMember, Lou Myers]
-
A.
Joe Hogue
Joe Hogue is a music producer known for his work on early recordings by pop artist Katy Perry (then performing as Katy Hudson).
-
B.
Phil Davis
Phil Davis is an English actor and director known for his character roles in film and television, including prominent work in British crime dramas and literary adaptations.
-
C.
Phil Davis
Phil Davis is a charming, quick-witted song-and-dance man and army veteran who partners with Bob Wallace in the classic musical film "White Christmas."
-
D.
Bryant Myers
Bryant Myers is a Puerto Rican Latin trap and reggaeton artist known for his gritty lyrics and collaborations with major urban artists.
-
E.
Kevin Myers
Kevin Myers is a central character in the American Pie film series, known as one of the core group of friends navigating relationships and adulthood.
- 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: Lou Myers Triple: [Cobb, castMember, Lou Myers]
Generated description
Lou Myers was an American actor best known for his role as Mr. Vernon Gaines on the television series "A Different World."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lou Myers Target entity description: Lou Myers was an American actor best known for his role as Mr. Vernon Gaines on the television series "A Different World."
-
A.
Joe Hogue
Joe Hogue is a music producer known for his work on early recordings by pop artist Katy Perry (then performing as Katy Hudson).
-
B.
Phil Davis
Phil Davis is a charming, quick-witted song-and-dance man and army veteran who partners with Bob Wallace in the classic musical film "White Christmas."
-
C.
Phil Davis
Phil Davis is an English actor and director known for his character roles in film and television, including prominent work in British crime dramas and literary adaptations.
-
D.
Bryant Myers
Bryant Myers is a Puerto Rican Latin trap and reggaeton artist known for his gritty lyrics and collaborations with major urban artists.
-
E.
Kevin Myers
Kevin Myers is a central character in the American Pie film series, known as one of the core group of friends navigating relationships and adulthood.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158eef48819083bdce283a363414 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f690ae408190966bb4fe8feaa7d2 |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f6022ecf38819080f0eb6a3a815c5b |
completed | May 2, 2026, 1:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f606560934819092ba4d4fa162b799 |
completed | May 2, 2026, 2:12 p.m. |
Created at: April 8, 2026, 9:49 p.m.