Triple
T16181118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KTM |
E392684
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | GasGas |
E535752
|
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: GasGas | Statement: [KTM, hasSubsidiary, GasGas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GasGas Context triple: [KTM, hasSubsidiary, GasGas]
-
A.
GasGas
chosen
GasGas is a Spanish motorcycle manufacturer best known for its off-road, enduro, and trial bikes, and more recently its presence in MotoGP.
-
B.
Gas
"Gas" is a 1940 painting by American realist artist Edward Hopper depicting a solitary gas station at dusk, emblematic of his themes of isolation and the quiet tension of modern American life.
-
C.
Gas
"Gas" is a painting by Belgian contemporary artist Luc Tuymans, known for its muted palette and unsettling atmosphere that reflects his interest in memory, history, and the lingering traces of violence.
-
D.
Gasoline
Gasoline is a 1958 poetry collection by Beat Generation writer Gregory Corso, known for its energetic, surreal, and rebellious verse.
-
E.
Gasoline
"Gasoline" is a dark, introspective pop song by American singer Halsey that explores themes of mental health, identity, and self-destruction.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205c92b48190b7125dbbcff3662e |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff0022148190bc1810e76cf6d994 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.