Triple
T5652519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vy |
E124537
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | Vy Tog |
E119737
|
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: Vy Tog | Statement: [Vy, subsidiary, Vy Tog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vy Tog Context triple: [Vy, subsidiary, Vy Tog]
-
A.
Vy Tog
chosen
Vy Tog is a Norwegian railway company that operates regional and intercity passenger train services, including routes through Oslo Central Station.
-
B.
Vaitogi
Vaitogi is a coastal village on the island of Tutuila in American Samoa, known for its dramatic sea cliffs and traditional Samoan culture.
-
C.
Vangunu
Vangunu is an Oceanic language of the Meso-Melanesian group spoken on Vangunu Island in the Solomon Islands.
-
D.
Viras
Viras is a squid-like alien kaiju from the Gamera film series, known as a leader of an invading extraterrestrial race that battles the giant turtle monster.
-
E.
Togoshi
Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d8a2588190b10de59edbc8841f |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d97b8dc8190865ff55071954b30 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.