Triple
T12155922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cubao MRT station |
E289573
|
entity |
| Predicate | hasJeepneyConnections |
P34620
|
FINISHED |
| Object | Cubao jeepney routes |
—
|
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: Cubao jeepney routes | Statement: [Cubao MRT station, hasJeepneyConnections, Cubao jeepney routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJeepneyConnections Context triple: [Cubao MRT station, hasJeepneyConnections, Cubao jeepney routes]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasBusServices
Indicates that one location or entity is served by bus routes or bus transportation provided by another.
-
C.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
D.
hasPublicTransitFunction
Indicates that something serves a role or provides a service related to public transportation operations or infrastructure.
-
E.
hasPublicTransitRoute
chosen
Indicates that there exists a public transportation route (such as a bus, train, or tram line) connecting or serving the related entities.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.