Triple
T6283688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Tom Club |
E140844
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Gary Pozner
Gary Pozner is a musician known for being a member of the American new wave band Tom Tom Club.
|
E581652
|
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: Gary Pozner | Statement: [Tom Tom Club, hasMember, Gary Pozner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gary Pozner Context triple: [Tom Tom Club, hasMember, Gary Pozner]
-
A.
Michael Berman
Michael Berman is a writer and contributor known for his work published in George magazine.
-
B.
Joseph Wechsler
Joseph Wechsler was an individual of sufficient local or historical significance to be recognized as a notable burial at Mount Olivet Cemetery in Frederick, Maryland.
-
C.
Alan Rubin
Alan Rubin was an American trumpeter best known for his work as a session musician and as a member of the original Saturday Night Live Band and The Blues Brothers.
-
D.
Daniel G. Bobrow
Daniel G. Bobrow was an influential American computer scientist and early artificial intelligence researcher known for his work on natural language understanding and AI programming systems.
-
E.
Jerome Sacks
Jerome Sacks is an American statistician known for his contributions to experimental design, statistical theory, and the development of computer experiments.
- 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: Gary Pozner Triple: [Tom Tom Club, hasMember, Gary Pozner]
Generated description
Gary Pozner is a musician known for being a member of the American new wave band Tom Tom Club.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gary Pozner Target entity description: Gary Pozner is a musician known for being a member of the American new wave band Tom Tom Club.
-
A.
Michael Berman
Michael Berman is a writer and contributor known for his work published in George magazine.
-
B.
Joseph Wechsler
Joseph Wechsler was an individual of sufficient local or historical significance to be recognized as a notable burial at Mount Olivet Cemetery in Frederick, Maryland.
-
C.
Alan Rubin
Alan Rubin was an American trumpeter best known for his work as a session musician and as a member of the original Saturday Night Live Band and The Blues Brothers.
-
D.
Daniel G. Bobrow
Daniel G. Bobrow was an influential American computer scientist and early artificial intelligence researcher known for his work on natural language understanding and AI programming systems.
-
E.
Jerome Sacks
Jerome Sacks is an American statistician known for his contributions to experimental design, statistical theory, and the development of computer experiments.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063fb6b1c8190b19a674c18fc9c53 |
completed | March 22, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5196864788190934e7c66d450dcf1 |
completed | March 26, 2026, 11:32 a.m. |
| NEDg | Description generation | batch_69c51e9932cc8190bce03a28097a2ddc |
completed | March 26, 2026, 11:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c51f1689dc8190bbd38cd7a5425224 |
completed | March 26, 2026, 11:57 a.m. |
Created at: March 22, 2026, 4:26 p.m.