Triple
T2331596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arbatsko–Pokrovskaya Line |
E44213
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Volokolamskaya
Volokolamskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya Line serving the northwestern part of the city.
|
E319578
|
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: Volokolamskaya | Statement: [Arbatsko–Pokrovskaya Line, hasStation, Volokolamskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volokolamskaya Context triple: [Arbatsko–Pokrovskaya Line, hasStation, Volokolamskaya]
-
A.
Rizhskaya
Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
-
B.
Kashirskaya
Kashirskaya is a Moscow Metro station that serves as an interchange point on the system’s Big Circle Line.
-
C.
Serpukhovskaya
Serpukhovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in central Moscow.
-
D.
Krasnopresnenskaya
Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
-
E.
Rubtsovsk
Rubtsovsk is an industrial city in Altai Krai, Russia, known as the birthplace of Raisa Gorbacheva and for its role as a regional agricultural and machinery center.
- 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: Volokolamskaya Triple: [Arbatsko–Pokrovskaya Line, hasStation, Volokolamskaya]
Generated description
Volokolamskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya Line serving the northwestern part of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Volokolamskaya Target entity description: Volokolamskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya Line serving the northwestern part of the city.
-
A.
Rizhskaya
Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
-
B.
Kashirskaya
Kashirskaya is a Moscow Metro station that serves as an interchange point on the system’s Big Circle Line.
-
C.
Serpukhovskaya
Serpukhovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in central Moscow.
-
D.
Krasnopresnenskaya
Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
-
E.
Rubtsovsk
Rubtsovsk is an industrial city in Altai Krai, Russia, known as the birthplace of Raisa Gorbacheva and for its role as a regional agricultural and machinery center.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc669956881908b8d9784d6a06acf |
completed | March 7, 2026, 6:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12ded5f9c8190a0de21b631d970b0 |
completed | March 11, 2026, 8:55 a.m. |
| NEDg | Description generation | batch_69b1316ee0708190bd27bb78f7f298d3 |
completed | March 11, 2026, 9:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1d6729f848190a275638f074c1729 |
completed | March 11, 2026, 8:54 p.m. |
Created at: March 4, 2026, 7:51 p.m.