Triple
T10879135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elektrozavodskaya |
E256873
|
entity |
| Predicate | isOnSectionBetween |
P74300
|
FINISHED |
| Object |
Baumanskaya
Baumanskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya line, known for its Stalinist-era architecture and heavy passenger traffic.
|
E890378
|
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: Baumanskaya | Statement: [Elektrozavodskaya, isOnSectionBetween, Baumanskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baumanskaya Context triple: [Elektrozavodskaya, isOnSectionBetween, Baumanskaya]
-
A.
Khoroshevskaya
Khoroshevskaya is a Moscow Metro station located on the Big Circle Line, serving the Khoroshyovsky District of the city.
-
B.
Sheremetevskaya
Sheremetevskaya is a Russian noble family name historically associated with the aristocracy of the Russian Empire.
-
C.
Kantemirovskaya
Kantemirovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the southern part of the city.
-
D.
Kaluzhskaya
Kaluzhskaya is a Moscow Metro station on the Kaluzhsko–Rizhskaya line, serving the southwestern part of the city.
-
E.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
- 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: Baumanskaya Triple: [Elektrozavodskaya, isOnSectionBetween, Baumanskaya]
Generated description
Baumanskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya line, known for its Stalinist-era architecture and heavy passenger traffic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baumanskaya Target entity description: Baumanskaya is a Moscow Metro station on the Arbatsko–Pokrovskaya line, known for its Stalinist-era architecture and heavy passenger traffic.
-
A.
Khoroshevskaya
Khoroshevskaya is a Moscow Metro station located on the Big Circle Line, serving the Khoroshyovsky District of the city.
-
B.
Sheremetevskaya
Sheremetevskaya is a Russian noble family name historically associated with the aristocracy of the Russian Empire.
-
C.
Kantemirovskaya
Kantemirovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the southern part of the city.
-
D.
Kaluzhskaya
Kaluzhskaya is a Moscow Metro station on the Kaluzhsko–Rizhskaya line, serving the southwestern part of the city.
-
E.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
- 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751af50448190906b47c16878208f |
completed | April 9, 2026, 7:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7e2322c8190a55605237ae6ce95 |
completed | April 15, 2026, 8:41 p.m. |
| NEDg | Description generation | batch_69e002709d38819099c4402d30824612 |
completed | April 15, 2026, 9:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e005873ba48190b8c24c77611562fa |
completed | April 15, 2026, 9:39 p.m. |
Created at: April 8, 2026, 9:21 p.m.