Triple
T5180830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pioneer Courthouse Square station |
E116914
|
entity |
| Predicate | isUrbanRailStop |
P49108
|
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: [Pioneer Courthouse Square station, isUrbanRailStop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanRailStop Context triple: [Pioneer Courthouse Square station, isUrbanRailStop, yes]
-
A.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
isPublicTransportStation
chosen
Indicates that a location functions as a station or stop used by public transportation services such as buses, trains, trams, or subways.
-
D.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
E.
isSuburbanStationOf
Indicates that a station is located in a suburban area and functionally serves as a subsidiary or outlying station of a main or central station.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799a322c8190b8a590cfe70761f5 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b529948190b86671ebe43f4734 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:45 p.m.