Triple
T5862830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flood |
E130315
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Daniel Lanois |
E124296
|
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: Daniel Lanois | Statement: [Flood, collaboratedWith, Daniel Lanois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Lanois Context triple: [Flood, collaboratedWith, Daniel Lanois]
-
A.
Daniel Lanois
chosen
Daniel Lanois is a Canadian record producer, musician, and songwriter renowned for his atmospheric, textural production work with artists such as U2, Bob Dylan, and Peter Gabriel.
-
B.
Mitchell Froom
Mitchell Froom is an American record producer and musician known for his innovative, atmospheric work with artists such as Crowded House, Suzanne Vega, and Los Lobos.
-
C.
Butch Vig
Butch Vig is an American record producer and musician best known for producing Nirvana's landmark album "Nevermind" and as the drummer for the alternative rock band Garbage.
-
D.
David Shaw
David Shaw is an American football coach best known for his successful tenure as head coach of Stanford University's football program in the 2010s.
-
E.
David Shaw
David Shaw was an American screenwriter known for his work in mid-20th-century film and television.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0358b11308190b2ef1c8febccc4b4 |
completed | March 22, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d12459481909eaaf52302686119 |
completed | March 24, 2026, 4:03 a.m. |
Created at: March 22, 2026, 3:56 p.m.