Triple
T31675178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Хорошёвская |
E808379
|
entity |
| Predicate | номерЛинии |
P40231
|
FINISHED |
| Object | 11 |
—
|
LITERAL 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: 11 | Statement: [Хорошёвская, номерЛинии, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: номерЛинии Context triple: [Хорошёвская, номерЛинии, 11]
-
A.
trackNumberWithinLine
Indicates the position or sequence number assigned to a track within a specific line or route.
-
B.
hasLineNumber
Indicates that something is associated with a specific line number, typically denoting its position within an ordered sequence such as lines of text or code.
-
C.
hasRailwayLineNumber
Indicates the specific identification number assigned to a railway line associated with an entity.
-
D.
railwayLineNumber
chosen
Indicates the identifying number assigned to a specific railway line within a rail network.
-
E.
lineName
Indicates the specific name or designation assigned to a particular line (such as a route, path, or service) that distinguishes it from other lines.
- F. None of above.
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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:02 p.m.