Triple
T38454359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blumentritt LRT station |
E912266
|
entity |
| Predicate | hasModeInterchange |
P201128
|
FINISHED |
| Object | jeepney |
—
|
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: jeepney | Statement: [Blumentritt LRT station, hasModeInterchange, jeepney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModeInterchange Context triple: [Blumentritt LRT station, hasModeInterchange, jeepney]
-
A.
hasInterchangeOptions
Indicates that an entity offers or is associated with alternative options that can be substituted or exchanged in its place.
-
B.
hasModeSwitching
Indicates that an entity supports changing between different operational modes or states.
-
C.
hasRailInterchangeFunction
Indicates that something serves as a location or facility where rail lines connect or intersect, allowing passengers or goods to transfer between them.
-
D.
hasRailMode
Indicates that an entity is associated with or supports transportation via rail-based modes (such as trains, trams, or subways).
-
E.
isInterchangeBetween
Indicates a relationship where something serves as a point or medium through which two or more entities can exchange or transfer items, information, or traffic between each other.
- F. None of above. chosen
Provenance (4 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_69f76e84e2dc81908badf05b3aafa9ea |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ffc894cef481908dae1d9cdc7d9d1f |
completed | May 9, 2026, 11:51 p.m. |
Created at: May 3, 2026, 4:31 p.m.