Triple
T20058148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odintsovo railway station |
E499394
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | town of Odintsovo |
—
|
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: town of Odintsovo | Statement: [Odintsovo railway station, serves, town of Odintsovo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: town of Odintsovo Context triple: [Odintsovo railway station, serves, town of Odintsovo]
-
A.
Odintsovo
chosen
Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
-
B.
city of Poshekhonye
The city of Poshekhonye is a small historic town in central Russia known for its traditional cheese production and location along the Sogozha River.
-
C.
city of Tutaev
The city of Tutaev is a historic town on the Volga River in central Russia, known for its preserved old architecture and role as a cultural center within Yaroslavl Oblast.
-
D.
Vladykino
Vladykino is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Vladykino district in the northeast of the city.
-
E.
city of Gavrilov-Yam
The city of Gavrilov-Yam is a small industrial and cultural center in central Russia, known historically for its textile and yarn production.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6637325908190aefc0e27e2ed5750 |
completed | April 20, 2026, 5:33 p.m. |
Created at: April 11, 2026, 3:38 p.m.