Triple
T18253668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caterpillar Inc. |
E437164
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | CAT |
—
|
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: CAT | Statement: [Caterpillar Inc., hasBrand, CAT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAT Context triple: [Caterpillar Inc., hasBrand, CAT]
-
A.
CAT
CAT is a branded express rail service that connects Vienna International Airport with the city center quickly and comfortably.
-
B.
CAT
chosen
CAT is a globally recognized industrial brand best known for its heavy construction machinery, engines, and rugged workwear.
-
C.
CAT
CAT is the National Rail station code for Caterham railway station in Surrey, England.
-
D.
CAT
CAT was the civilian airline operated by the CIA in East Asia during the early Cold War, later becoming known as Air America.
-
E.
CAT
CAT is a highly competitive national-level entrance examination in India used for admission to postgraduate management programs such as MBAs at premier institutes.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd82f81c81909ad4455954bd8caa |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:33 a.m.