Triple
T19726000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Severobaikalsk |
E473727
|
entity |
| Predicate | railConnection |
P848
|
FINISHED |
| Object | Tynda |
—
|
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: Tynda | Statement: [Severobaikalsk, railConnection, Tynda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tynda Context triple: [Severobaikalsk, railConnection, Tynda]
-
A.
Tynda
chosen
Tynda is a town in Russia’s Far East known as a major junction on the Baikal–Amur Mainline railway.
-
B.
Tywon
Tywon is the given first name of American professional basketball player Ty Lawson.
-
C.
Tyrena
Tyrena is a notable city on the planet Corellia in the Star Wars universe, known for its urban sprawl and role as a regional hub.
-
D.
Tarutyne
Tarutyne is an urban-type settlement in Odesa Oblast, southwestern Ukraine, serving as a local administrative and cultural center.
-
E.
Tyana
Tyana was an ancient city in south-central Anatolia, historically significant as a regional center and later as a notable urban hub within the Roman Empire.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f7bedc81908f784832c0fc10a1 |
completed | April 20, 2026, 3:44 p.m. |
Created at: April 10, 2026, 1:46 p.m.