Triple
T2045763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tagansko–Krasnopresnenskaya Line |
E45446
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object |
Kotelniki
Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
|
E230199
|
NE FINISHED |
How this triple was built (4 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, hasTerminus, Kotelniki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kotelniki Context triple: [Tagansko–Krasnopresnenskaya Line, hasTerminus, Kotelniki]
-
A.
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.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Wielka Krokiew
Wielka Krokiew is a major ski jumping hill in Zakopane, Poland, known for hosting prominent international ski jumping competitions.
-
D.
Olecko
Olecko is a small town in northeastern Poland known for its lakeside setting and location within the historic region of Masuria.
-
E.
Jastarnia
Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kotelniki Triple: [Tagansko–Krasnopresnenskaya Line, hasTerminus, Kotelniki]
Generated description
Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kotelniki Target entity description: Kotelniki is a Moscow Metro station serving as the southeastern terminus of the Tagansko–Krasnopresnenskaya Line in the town of Kotelniki, just outside Moscow.
-
A.
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.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Wielka Krokiew
Wielka Krokiew is a major ski jumping hill in Zakopane, Poland, known for hosting prominent international ski jumping competitions.
-
D.
Olecko
Olecko is a small town in northeastern Poland known for its lakeside setting and location within the historic region of Masuria.
-
E.
Jastarnia
Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
- F. None of above. chosen
Provenance (5 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_69ae200125f081909ab40b6a04adaa25 |
completed | March 9, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69ae242933288190ad1f2c9f4ce1e968 |
completed | March 9, 2026, 1:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae248a2b8481908fa4b0c000971d11 |
completed | March 9, 2026, 1:38 a.m. |
Created at: March 4, 2026, 7:39 p.m.