Triple
T22575281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Company Flow |
E544377
|
entity |
| Predicate | hasFormerMember |
P1168
|
FINISHED |
| Object | Mr. Len |
—
|
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: Mr. Len | Statement: [Company Flow, hasFormerMember, Mr. Len]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Len Context triple: [Company Flow, hasFormerMember, Mr. Len]
-
A.
Mr. Len
chosen
Mr. Len is an American DJ and producer best known as a founding member of the influential underground hip hop group Company Flow.
-
B.
Mr. Long
Mr. Long is a 2017 Japanese-Taiwanese crime drama film starring Chang Chen as a Taiwanese hitman who hides out in a small Japanese town and bonds with local residents while posing as a noodle chef.
-
C.
Mr. Franks
Mr. Franks is a music producer best known for his work with the hip-hop collective Legend.
-
D.
Bobby Lennox
Bobby Lennox is a Scottish former footballer best known as a prolific winger for Celtic FC and a member of their legendary 1967 European Cup–winning "Lisbon Lions" team.
-
E.
Mr. Bryles
Mr. Bryles is the central character in the 1999-set story "Class of 1999," around whom the main events and conflicts revolve.
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15fec296481908a6101b02e5bedaa |
completed | April 29, 2026, 1:33 a.m. |
Created at: April 16, 2026, 8:53 p.m.