Triple
T15592221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulitsa Milashenkova |
E374772
|
entity |
| Predicate | isPassengerStop |
P119352
|
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: [Ulitsa Milashenkova, isPassengerStop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPassengerStop Context triple: [Ulitsa Milashenkova, isPassengerStop, yes]
-
A.
isPassengerStationFor
Indicates that a station serves as a boarding and alighting point for passengers on a particular transportation line or service.
-
B.
isPassengerStationCode
Indicates that a given code is officially assigned to identify a particular passenger station.
-
C.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
D.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
E.
stopsAtStation
Indicates that a vehicle or service halts at a particular station as part of its route or schedule.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5e43d48190a8fd367f13f1c7e1 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:12 a.m.