Triple
T14045834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Stewart |
E337952
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Fuel |
E1076643
|
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: Fuel | Statement: [Tommy Stewart, memberOf, Fuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuel Context triple: [Tommy Stewart, memberOf, Fuel]
-
A.
Fuel
chosen
Fuel is an American rock band, prominent in the late 1990s and early 2000s post-grunge scene, known for hits like "Hemorrhage (In My Hands)" and "Shimmer."
-
B.
Gasoline
Gasoline is a 1958 poetry collection by Beat Generation writer Gregory Corso, known for its energetic, surreal, and rebellious verse.
-
C.
Gasoline
"Gasoline" is a dark, introspective pop song by American singer Halsey that explores themes of mental health, identity, and self-destruction.
-
D.
GasGas
GasGas is a Spanish motorcycle manufacturer best known for its off-road, enduro, and trial bikes, and more recently its presence in MotoGP.
-
E.
Jet-A kerosene
Jet-A kerosene is a widely used aviation turbine fuel for jet and turboprop aircraft, characterized by its high energy density, controlled combustion properties, and strict performance and safety specifications.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de312df37081909f45ce3e219af5dc |
completed | April 14, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb65c1a90819097754497f07f5312 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:20 p.m.