Triple
T23624893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenosha station |
E583434
|
entity |
| Predicate | adjacentCityOnLine |
P153320
|
FINISHED |
| Object | Winthrop Harbor station |
—
|
NE NERFINISHED |
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: Winthrop Harbor station | Statement: [Kenosha station, adjacentCityOnLine, Winthrop Harbor station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentCityOnLine Context triple: [Kenosha station, adjacentCityOnLine, Winthrop Harbor station]
-
A.
adjacentStationOnLineD
Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
-
B.
adjacentStationOnLine
Indicates that one station is directly next to another station along the same transit line, with no other station in between.
-
C.
adjacentStationOnDistrictLine
Indicates that one station is directly next to another station along the District Line, with no other stations in between on that line.
-
D.
adjacentStationOnLine2
Indicates that one station is directly next to another station along line 2 in a transit or rail network.
-
E.
adjacentCityNorth
Indicates that one city is directly to the north of another city and shares a common boundary or is immediately neighboring it in that direction.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17c993c8190bf9ee3201869d240 |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f138b8c9248190b059bc38a9a50958 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 17, 2026, 6:46 p.m.