Triple
T24368433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago–Pacific Northwest route |
E614263
|
entity |
| Predicate | headquartersRailroad |
P22571
|
FINISHED |
| Object | Milwaukee, Wisconsin |
—
|
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: Milwaukee, Wisconsin | Statement: [Chicago–Pacific Northwest route, headquartersRailroad, Milwaukee, Wisconsin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: headquartersRailroad Context triple: [Chicago–Pacific Northwest route, headquartersRailroad, Milwaukee, Wisconsin]
-
A.
headquartersRailroadCity
Indicates that a railroad company has its main headquarters located in a particular city.
-
B.
hasRailwayHeadquarters
chosen
Indicates that a railway organization or system has its main administrative or operational headquarters located at a specified place.
-
C.
railwayDivisionHeadquartersOf
Indicates that one location serves as the administrative headquarters for a specified railway division.
-
D.
headquartersStation
Indicates that a particular station serves as the main headquarters location for an organization or entity.
-
E.
headquartersFor
Indicates that a location serves as the main administrative center or base of operations for an organization or entity.
- 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_69e2d7e1e010819098b95eb3f905943d |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2938994c081909730d1e02e823dfd |
completed | April 29, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:01 a.m.