Triple
T15900786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Waitresses |
E385582
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Dan Klayman
Dan Klayman is a musician best known as a member of the new wave band The Waitresses.
|
E1220230
|
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: Dan Klayman | Statement: [The Waitresses, hasMember, Dan Klayman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Klayman Context triple: [The Waitresses, hasMember, Dan Klayman]
-
A.
Rich Kleiman
Rich Kleiman is an American sports agent and entrepreneur best known as Kevin Durant’s longtime business partner and co-founder of the sports and entertainment company Boardroom and the investment firm Thirty Five Ventures.
-
B.
Jay Klaitz
Jay Klaitz is an American actor known for his work in theater, film, and television, including roles in Broadway productions and various character parts on screen.
-
C.
Michael Klein
Michael Klein is the father of Canadian author and activist Naomi Klein.
-
D.
Martin Brinkler
Martin Brinkler is a film editor known for his work on the shark thriller "47 Meters Down: Uncaged."
-
E.
Michael Kagan
Michael Kagan is an Israeli technologist and entrepreneur best known as the co-founder and longtime chief technology officer of high-performance networking company Mellanox Technologies.
- 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: Dan Klayman Triple: [The Waitresses, hasMember, Dan Klayman]
Generated description
Dan Klayman is a musician best known as a member of the new wave band The Waitresses.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dan Klayman Target entity description: Dan Klayman is a musician best known as a member of the new wave band The Waitresses.
-
A.
Rich Kleiman
Rich Kleiman is an American sports agent and entrepreneur best known as Kevin Durant’s longtime business partner and co-founder of the sports and entertainment company Boardroom and the investment firm Thirty Five Ventures.
-
B.
Jay Klaitz
Jay Klaitz is an American actor known for his work in theater, film, and television, including roles in Broadway productions and various character parts on screen.
-
C.
Michael Klein
Michael Klein is the father of Canadian author and activist Naomi Klein.
-
D.
Martin Brinkler
Martin Brinkler is a film editor known for his work on the shark thriller "47 Meters Down: Uncaged."
-
E.
Michael Kagan
Michael Kagan is an Israeli technologist and entrepreneur best known as the co-founder and longtime chief technology officer of high-performance networking company Mellanox Technologies.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563cd2f081909404d724ecc8785a |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067948b308190a434cdf1d45ebef4 |
completed | May 10, 2026, 11:10 a.m. |
| NEDg | Description generation | batch_6a00686f87408190b7d8a41cd54735d8 |
completed | May 10, 2026, 11:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a006b6edd7081908730363b267253dd |
completed | May 10, 2026, 11:26 a.m. |
Created at: April 10, 2026, 4:51 a.m.