Triple
T16996202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setra |
E412320
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Neoplan |
E212631
|
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: Neoplan | Statement: [Setra, competitor, Neoplan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neoplan Context triple: [Setra, competitor, Neoplan]
-
A.
Neoplan
chosen
Neoplan is a German bus and coach manufacturer renowned for its innovative, high-end touring and city buses.
-
B.
Neoplan Polska
Neoplan Polska was a Polish bus manufacturer that later evolved into Solaris Bus & Coach, a well-known European producer of city and intercity buses.
-
C.
Scammell
Scammell is an English surname borne by various notable individuals, including figures in American Revolutionary history and British industry.
-
D.
Suter
Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
-
E.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d2879af081909665f9f838bcfbe7 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc18e6988190b42b3d251cf00b98 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.