Triple
T12414566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viewliner |
E296601
|
entity |
| Predicate | usedOnService |
P2367
|
FINISHED |
| Object | Silver Star |
E6322
|
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: Silver Star | Statement: [Viewliner, usedOnService, Silver Star]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silver Star Context triple: [Viewliner, usedOnService, Silver Star]
-
A.
Silver Star
chosen
Silver Star is a long-distance Amtrak passenger train that runs along the U.S. East Coast, connecting New York City with Florida.
-
B.
Silver Star
Silver Star is a large steel roller coaster at Europa-Park in Germany, known for its high speed, significant height, and smooth hypercoaster design.
-
C.
Silver Star
The Silver Star is a high-level U.S. military decoration awarded for gallantry in action against an enemy of the United States.
-
D.
Silver Wings
"Silver Wings" is a classic country song by Merle Haggard, known for its melancholic melody and themes of love and loss.
-
E.
What Price Glory
What Price Glory is a 1926 silent war-comedy film set during World War I, best known for its blend of battlefield drama and bawdy humor.
- 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.