Triple
T2045794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tagansko–Krasnopresnenskaya Line |
E45446
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Kotelniki |
E230199
|
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: Kotelniki | Statement: [Tagansko–Krasnopresnenskaya Line, hasStation, Kotelniki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kotelniki Context triple: [Tagansko–Krasnopresnenskaya Line, hasStation, Kotelniki]
-
A.
Kotelniki
chosen
Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
-
B.
Kutyna
Kutyna is the surname of Donald J. Kutyna, a U.S. Air Force general known for his role in the investigation of the Space Shuttle Challenger disaster.
-
C.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
D.
Wielka Krokiew
Wielka Krokiew is a major ski jumping hill in Zakopane, Poland, known for hosting prominent international ski jumping competitions.
-
E.
Kuzminki
Kuzminki is a Moscow Metro station on the Tagansko–Krasnopresnenskaya Line serving the Kuzminki District in southeastern Moscow.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9728f688190939d7c4df524f9b4 |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58c2cb688190ae3320bbf4e0dfa9 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:39 p.m.