Triple
T6976269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modest Mouse |
E161724
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object |
Tom Peloso
Tom Peloso is an American multi-instrumentalist best known as a longtime member of the indie rock band Modest Mouse.
|
E633801
|
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: Tom Peloso | Statement: [Modest Mouse, member, Tom Peloso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Peloso Context triple: [Modest Mouse, member, Tom Peloso]
-
A.
Tom Werner
Tom Werner is an American television producer and businessman best known as a co-owner and chairman of the Boston Red Sox and Liverpool FC.
-
B.
Chub Feeney
Chub Feeney was a longtime Major League Baseball executive who served as president of the National League from 1970 to 1986.
-
C.
Daniel Akaka
Daniel Akaka was a long-serving U.S. Senator from Hawaii known for his advocacy on Native Hawaiian rights and veterans’ issues.
-
D.
Ron Pelosi
Ron Pelosi is an American businessman and political figure from California, known for his involvement in local Democratic politics and as a member of the prominent Pelosi family.
-
E.
Matt Santos
Matt Santos is a fictional U.S. congressman who becomes President in the television series "The West Wing."
- 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: Tom Peloso Triple: [Modest Mouse, member, Tom Peloso]
Generated description
Tom Peloso is an American multi-instrumentalist best known as a longtime member of the indie rock band Modest Mouse.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Peloso Target entity description: Tom Peloso is an American multi-instrumentalist best known as a longtime member of the indie rock band Modest Mouse.
-
A.
Tom Werner
Tom Werner is an American television producer and businessman best known as a co-owner and chairman of the Boston Red Sox and Liverpool FC.
-
B.
Chub Feeney
Chub Feeney was a longtime Major League Baseball executive who served as president of the National League from 1970 to 1986.
-
C.
Daniel Akaka
Daniel Akaka was a long-serving U.S. Senator from Hawaii known for his advocacy on Native Hawaiian rights and veterans’ issues.
-
D.
Ron Pelosi
Ron Pelosi is an American businessman and political figure from California, known for his involvement in local Democratic politics and as a member of the prominent Pelosi family.
-
E.
Matt Santos
Matt Santos is a fictional U.S. congressman who becomes President in the television series "The West Wing."
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db677bbc8190a084b6951e5c3182 |
completed | March 27, 2026, 7:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761ab41b0819084d26c10bb763f8e |
completed | March 28, 2026, 5:05 a.m. |
| NEDg | Description generation | batch_69c763b0d5cc8190bdd82fc8a5a95ef1 |
completed | March 28, 2026, 5:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76435fd2c819099143ea12f21d095 |
completed | March 28, 2026, 5:16 a.m. |
Created at: March 27, 2026, 2:31 p.m.