Triple
T36675585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden State (passenger train) |
E905532
|
entity |
| Predicate | routeTerminusCity |
P1866
|
FINISHED |
| Object | Chicago |
—
|
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: Chicago | Statement: [Golden State (passenger train), routeTerminusCity, Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeTerminusCity Context triple: [Golden State (passenger train), routeTerminusCity, Chicago]
-
A.
notableTerminusCity
Indicates that a city is notably recognized as a terminus (endpoint) of a route, line, or network.
-
B.
terminusCity
chosen
Indicates that a transportation route or service ends or has its final stop in a particular city.
-
C.
terminalCityRegion
Indicates that a city serves as the terminal (end-point) location within a specified region for a route, line, or connection.
-
D.
transportTerminusFor
Indicates that a location serves as the endpoint or final stop for a particular transport route or service.
-
E.
terminusCityArea
Indicates that a city area serves as the terminal or end-point location for a route, line, or journey.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.