Triple
T6605862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Starr |
E149115
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Dirt (album) |
E568651
|
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: Dirt (album) | Statement: [Mike Starr, notableWork, Dirt (album)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dirt (album) Context triple: [Mike Starr, notableWork, Dirt (album)]
-
A.
Dirt
Dirt is a music album titled "Dirt" released by the band Rooster.
-
B.
Dirt
Dirt is a critically acclaimed 1992 grunge/metal album by Alice in Chains known for its dark themes, heavy riffs, and influential role in defining the Seattle sound.
-
C.
Dirt
"Dirt" is a reflective country ballad by Florida Georgia Line that focuses on themes of home, roots, and the passage of life.
-
D.
Dirt (Alice in Chains album)
chosen
Dirt is the critically acclaimed 1992 heavy metal/grunge album by Alice in Chains, known for its dark themes, heavy riffs, and influence on the Seattle sound.
-
E.
Hollywood Dirt
"Hollywood Dirt" is a romantic drama film produced and directed by Tosca Musk, adapted from Alessandra Torre’s bestselling novel about a small-town girl and a Hollywood star whose worlds collide during a movie shoot in rural Georgia.
- 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af143d5c8190b62602602510b1cb |
completed | March 27, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbce25b481908d600d38d3c5b871 |
completed | March 27, 2026, 6:26 p.m. |
Created at: March 27, 2026, 1:56 p.m.