Triple
T10681414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrovagonmash |
E251763
|
entity |
| Predicate | servesTransportSystem |
P14525
|
FINISHED |
| Object | Sofia Metro |
E165788
|
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: Sofia Metro | Statement: [Metrovagonmash, servesTransportSystem, Sofia Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sofia Metro Context triple: [Metrovagonmash, servesTransportSystem, Sofia Metro]
-
A.
Sofia Metro
chosen
Sofia Metro is the rapid transit system serving Bulgaria’s capital city, providing high-capacity urban rail transport across Sofia and its metropolitan area.
-
B.
Samara Metro
Samara Metro is the rapid transit system serving the city of Samara, Russia, providing urban rail transportation across several key districts.
-
C.
Bucharest Metro
The Bucharest Metro is the rapid transit system serving Romania’s capital city, providing high-capacity urban rail transport across Bucharest.
-
D.
Saint Petersburg Metro
The Saint Petersburg Metro is a major rapid transit system in Saint Petersburg, Russia, renowned for its deep underground stations and ornate, palace-like architecture.
-
E.
Novosibirsk Metro
Novosibirsk Metro is a rapid transit system in Novosibirsk, Russia, serving as a key component of the city's public transportation network with several lines and stations across the urban area.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fcc30be481909922844b539b622d |
completed | April 9, 2026, 1:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998bfc27c8190a9d3e77fbe544a6d |
completed | April 11, 2026, 12:41 a.m. |
Created at: April 8, 2026, 9:10 p.m.