Triple
T2167528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serpukhovsko–Timiryazevskaya Line |
E46944
|
entity |
| Predicate | lineColour |
P34402
|
FINISHED |
| Object | gray |
—
|
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: gray | Statement: [Serpukhovsko–Timiryazevskaya Line, lineColour, gray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineColour Context triple: [Serpukhovsko–Timiryazevskaya Line, lineColour, gray]
-
A.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
B.
lineLetterColorStandard
Indicates the standard or default color assigned to the letter representation of a particular line.
-
C.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
-
D.
lineSymbol
Indicates that one entity is used as a line-style or line-representation symbol for another entity.
-
E.
lineType
Indicates the specific category or style of a line used in a representation, such as its function or visual convention.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.