Triple
T34994491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vancouver–Prince George |
E1009484
|
entity |
| Predicate | hasRouteSegmentThrough |
P51968
|
FINISHED |
| Object | Vancouver metropolitan area |
—
|
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: Vancouver metropolitan area | Statement: [Vancouver–Prince George, hasRouteSegmentThrough, Vancouver metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteSegmentThrough Context triple: [Vancouver–Prince George, hasRouteSegmentThrough, Vancouver metropolitan area]
-
A.
hasSegmentOn
chosen
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
B.
hasSegmentWith
Indicates that an entity contains or includes at least one segment that satisfies a specified condition or matches a given segment.
-
C.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
D.
hasSegmentFrom
Indicates that something includes or contains a segment that originates from or is derived from another specified source.
-
E.
hasSegmentBasedOn
Indicates that one segment is derived from, modeled after, or constructed using another segment as its basis.
- 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_69f76dca50dc8190b71f39defe186be8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: May 3, 2026, 4:01 p.m.