Triple
T3672839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stripes |
E77918
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Len Blum |
E342006
|
NE FINISHED |
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: Len Blum | Statement: [Stripes, writer, Len Blum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Len Blum Context triple: [Stripes, writer, Len Blum]
-
A.
Len Blum
chosen
Len Blum is a Canadian screenwriter known for his work on numerous comedy films, including the 2006 reboot of The Pink Panther.
-
B.
Michael Blum
Michael Blum is best known as the husband of comedian and actress Julia Sweeney.
-
C.
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.
-
D.
Johnny Gandelsman
Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
-
E.
Robert Blum
Robert Blum was the son of French politician and former Prime Minister Léon Blum.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42f82548190b4d5f0fe7250decb |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89b0441881908b87c7a62434e79a |
completed | March 21, 2026, 12:06 p.m. |
Created at: March 8, 2026, 3:25 p.m.