Triple
T10192011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novogireyevo |
E238058
|
entity |
| Predicate | railwayLineColor |
P34402
|
FINISHED |
| Object | yellow |
—
|
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: yellow | Statement: [Novogireyevo, railwayLineColor, yellow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayLineColor Context triple: [Novogireyevo, railwayLineColor, yellow]
-
A.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
railwaySignColor
Indicates the color attribute assigned to a particular railway sign.
-
C.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
D.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
E.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc4fb808190aae2e4b84be96f83 |
completed | April 2, 2026, 4:17 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:13 p.m.