Triple
T27902010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsawwassen–Duke Point route |
E705659
|
entity |
| Predicate | connectsCityRegion |
P112692
|
FINISHED |
| Object | Vancouver 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 area | Statement: [Tsawwassen–Duke Point route, connectsCityRegion, Vancouver area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCityRegion Context triple: [Tsawwassen–Duke Point route, connectsCityRegion, Vancouver area]
-
A.
connectsRegionalCity
Indicates a relationship where one entity serves as a link or transport route between a regional city and another location.
-
B.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
C.
linkedCityRegion
Indicates that a city is associated with, belongs to, or is administratively connected to a specific region.
-
D.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
E.
connectsProvinceOrRegion
chosen
Indicates that one entity serves to link or provide a connection between a specific province or region and another entity.
- 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_69ef96b490ac8190a412d04c5d009f3e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: April 27, 2026, 6:42 p.m.