Triple
T17512953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babes in Toyland |
E426495
|
entity |
| Predicate | hasFormerMember |
P1168
|
FINISHED |
| Object | Chris Holetz |
—
|
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: Chris Holetz | Statement: [Babes in Toyland, hasFormerMember, Chris Holetz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Holetz Context triple: [Babes in Toyland, hasFormerMember, Chris Holetz]
-
A.
Chris Holetz
chosen
Chris Holetz is a musician best known for playing in the American punk-influenced alternative rock band Babes in Toyland.
-
B.
Michael Holzer
Michael Holzer is an architect best known as one of the founders of the avant-garde Austrian architecture firm Coop Himmelb(l)au.
-
C.
Scott Huler
Scott Huler is an American author and journalist known for his narrative nonfiction works that often explore science, technology, and culture.
-
D.
Chris Hellman
Chris Hellman is a philanthropist and former ballet dancer known for her support of the arts, particularly through her work with the San Francisco Ballet and other cultural institutions.
-
E.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525d29fc819080851bf744bc78ed |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:49 a.m.