Triple
T15389282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very Good Girls |
E367996
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Michael Taylor
Michael Taylor is a film editor known for his work on movies such as the coming-of-age drama "Very Good Girls."
|
E1154815
|
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: Michael Taylor | Statement: [Very Good Girls, editor, Michael Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Taylor Context triple: [Very Good Girls, editor, Michael Taylor]
-
A.
Mike Taylor
Mike Taylor is a film editor known for his work on the acclaimed British gangster film "The Long Good Friday."
-
B.
Mike Taylor
Mike Taylor is a songwriter best known for co-writing John Denver’s classic folk song "Rocky Mountain High."
-
C.
David Taylor
David Taylor is a songwriter credited as one of the writers of Beyoncé’s hit empowerment anthem “Run the World (Girls).”
-
D.
Ben Taylor
Ben Taylor was an early 20th-century American baseball figure known for his role in the Negro leagues, including leadership and organizational contributions that helped establish prominent Black baseball teams.
-
E.
Glen Taylor
Glen Taylor is an American billionaire businessman and politician best known as the longtime owner of the NBA’s Minnesota Timberwolves and WNBA’s Minnesota Lynx.
- 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: Michael Taylor Triple: [Very Good Girls, editor, Michael Taylor]
Generated description
Michael Taylor is a film editor known for his work on movies such as the coming-of-age drama "Very Good Girls."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Taylor Target entity description: Michael Taylor is a film editor known for his work on movies such as the coming-of-age drama "Very Good Girls."
-
A.
Mike Taylor
Mike Taylor is a film editor known for his work on the acclaimed British gangster film "The Long Good Friday."
-
B.
Mike Taylor
Mike Taylor is a songwriter best known for co-writing John Denver’s classic folk song "Rocky Mountain High."
-
C.
David Taylor
David Taylor is a songwriter credited as one of the writers of Beyoncé’s hit empowerment anthem “Run the World (Girls).”
-
D.
Ben Taylor
Ben Taylor was an early 20th-century American baseball figure known for his role in the Negro leagues, including leadership and organizational contributions that helped establish prominent Black baseball teams.
-
E.
Glen Taylor
Glen Taylor is an American billionaire businessman and politician best known as the longtime owner of the NBA’s Minnesota Timberwolves and WNBA’s Minnesota Lynx.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e761b688190893a81246b735b76 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff134e37d881909f373b90a99fc067 |
completed | May 9, 2026, 10:58 a.m. |
| NEDg | Description generation | batch_69ff141b025c8190ac5ac9400ff36133 |
completed | May 9, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff1519100c819083ee0342bf25d89e |
completed | May 9, 2026, 11:06 a.m. |
Created at: April 10, 2026, 3:19 a.m.