Triple
T19250156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amur–Yakutsk Mainline |
E481366
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Tommot |
—
|
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: Tommot | Statement: [Amur–Yakutsk Mainline, terminus, Tommot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tommot Context triple: [Amur–Yakutsk Mainline, terminus, Tommot]
-
A.
Tommot
chosen
Tommot is a small town in Russia’s Sakha Republic, known as a transport hub on the Amur–Yakutsk Mainline railway and a gateway to the southern Yakutia region.
-
B.
Tommo
Tommo is a familiar diminutive nickname commonly used for people named Thomas, especially in British and Australian contexts.
-
C.
Toomai
Toomai is a young elephant handler’s son from Rudyard Kipling’s *The Jungle Book*, known for his bravery and his special bond with elephants.
-
D.
Tommen
Tommen is a fictional young king from George R. R. Martin’s "A Song of Ice and Fire" series and its TV adaptation "Game of Thrones," known as the gentle and impressionable youngest son of Cersei Lannister.
-
E.
Meeko
Meeko is the mischievous raccoon companion of Pocahontas in Disney's animated film "Pocahontas."
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb3001308190913e24343769be8d |
completed | April 20, 2026, 10:08 a.m. |
Created at: April 10, 2026, 1:27 p.m.