Triple
T9870649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma-Atinskaya |
E239946
|
entity |
| Predicate | hasTurnbackSidings |
P90976
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Alma-Atinskaya, hasTurnbackSidings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurnbackSidings Context triple: [Alma-Atinskaya, hasTurnbackSidings, yes]
-
A.
hasRailYard
Indicates that one entity possesses, contains, or includes a rail yard as part of its facilities or infrastructure.
-
B.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
C.
hasSwitchbacks
Indicates that a path, road, or trail includes sharp, back-and-forth turns (zigzags) used to navigate steep terrain.
-
D.
hasParkingLotOnBothSidesOfTracks
Indicates that there are parking lots located on both sides of the railway tracks at a given location.
-
E.
hasDepartureSide
Indicates the side or direction from which an entity departs or leaves a location.
- F. None of above. chosen
Provenance (4 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d62628819094786a49b9bcd09b |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:36 p.m.