Triple
T20118523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yo La Tengo |
E490532
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | James McNew |
—
|
NE NERFINISHED |
How this triple was built (2 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: James McNew | Statement: [Yo La Tengo, hasMember, James McNew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James McNew Context triple: [Yo La Tengo, hasMember, James McNew]
-
A.
James McNew
chosen
James McNew is an American musician best known as the longtime bassist for the indie rock band Yo La Tengo and for his solo project Dump.
-
B.
Christopher Shea
Christopher Shea was an American child actor best known for voicing Linus van Pelt in several classic Peanuts animated television specials.
-
C.
Christopher Young
Christopher Young is an American film composer renowned for his atmospheric and often darkly dramatic scores across horror, thriller, and action movies.
-
D.
Louis Mellis
Louis Mellis is a British screenwriter best known for co-writing the acclaimed crime film "Sexy Beast."
-
E.
Mike Kellin
Mike Kellin was an American character actor known for his prolific work in film, television, and theater from the 1950s through the 1970s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6673c32bc8190a52875961fbcc5e2 |
completed | April 20, 2026, 5:49 p.m. |
Created at: April 11, 2026, 11:30 p.m.