Triple
T33377624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of San Mateo |
E854677
|
entity |
| Predicate | hasCaltrainStation |
P726
|
FINISHED |
| Object | San Mateo 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: San Mateo station | Statement: [City of San Mateo, hasCaltrainStation, San Mateo station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaltrainStation Context triple: [City of San Mateo, hasCaltrainStation, San Mateo station]
-
A.
hasMBTACommuterRailTerminus
Indicates that one entity serves as the endpoint or final stop of an MBTA Commuter Rail line for the other entity.
-
B.
hasRailStation
chosen
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
isSuburbanRailStation
Indicates that a location functions as a railway station serving suburban or commuter rail services, typically connecting outlying areas with an urban center.
-
D.
hasAmtrakStationStatus
Indicates whether and how an entity is served by an Amtrak station, such as its operational or service status.
-
E.
amtrakStation
Indicates that one entity is an Amtrak train station serving the other entity or located at the specified place.
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 1:35 a.m.