Triple
T12414540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viewliner |
E296601
|
entity |
| Predicate | hasSubclass |
P1244
|
FINISHED |
| Object | Viewliner II |
E296601
|
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: Viewliner II | Statement: [Viewliner, hasSubclass, Viewliner II]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viewliner II Context triple: [Viewliner, hasSubclass, Viewliner II]
-
A.
Viewliner
chosen
Viewliner is a class of single-level passenger railcars used primarily by Amtrak for long-distance overnight service in the United States.
-
B.
Scotch tape
Scotch tape is a popular brand of transparent adhesive tape commonly used for household, office, and craft applications.
-
C.
Bondo
Bondo is a town in western Kenya’s Nyanza region, known as an administrative and commercial center near Lake Victoria.
-
D.
Glue
"Glue" is a novel by Scottish author Irvine Welsh that follows the intertwined lives of four working-class friends in Edinburgh over several decades.
-
E.
Uhu
Uhu was the nickname of the Heinkel He 219, a German World War II night fighter aircraft notable for its advanced radar and effectiveness against Allied bombers.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6c4f6c8190bc99d3f7b64205c3 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6348ccaf88190aeb0dfb7fe1d8dec |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.