Triple
T14611789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take 6 |
E342978
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Mark Kibble
Mark Kibble is an American gospel singer and arranger best known as a longtime member and vocal arranger of the a cappella group Take 6.
|
E1115985
|
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: Mark Kibble | Statement: [Take 6, hasPart, Mark Kibble]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Kibble Context triple: [Take 6, hasPart, Mark Kibble]
-
A.
John Carlisle
John Carlisle was a Scottish actor known for his work in British television and theatre, and for being married to actress Janet Leigh.
-
B.
Stephen Doughty
Stephen Doughty is a British Labour Party politician who has served as a Member of Parliament and held various shadow ministerial roles.
-
C.
Grant Bardsley
Grant Bardsley is a British voice actor best known for voicing the protagonist Taran in Disney’s animated film "The Black Cauldron."
-
D.
Adam Kendall
Adam Kendall is a musician best known for his past role as a member of the experimental metal band Neurosis.
-
E.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
- 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: Mark Kibble Triple: [Take 6, hasPart, Mark Kibble]
Generated description
Mark Kibble is an American gospel singer and arranger best known as a longtime member and vocal arranger of the a cappella group Take 6.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Kibble Target entity description: Mark Kibble is an American gospel singer and arranger best known as a longtime member and vocal arranger of the a cappella group Take 6.
-
A.
John Carlisle
John Carlisle was a Scottish actor known for his work in British television and theatre, and for being married to actress Janet Leigh.
-
B.
Stephen Doughty
Stephen Doughty is a British Labour Party politician who has served as a Member of Parliament and held various shadow ministerial roles.
-
C.
Grant Bardsley
Grant Bardsley is a British voice actor best known for voicing the protagonist Taran in Disney’s animated film "The Black Cauldron."
-
D.
Adam Kendall
Adam Kendall is a musician best known for his past role as a member of the experimental metal band Neurosis.
-
E.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb450e6588190a94488d8e71888c8 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf0763ca081909fa8bcbdc46f2fac |
completed | May 8, 2026, 2:17 p.m. |
| NEDg | Description generation | batch_69fdf376f8a08190b28804213316459f |
completed | May 8, 2026, 2:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdf42f57fc81908f7b44f9795bc28a |
completed | May 8, 2026, 2:33 p.m. |
Created at: April 10, 2026, 1:25 a.m.