Triple
T34721092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viana do Castelo station |
E1000914
|
entity |
| Predicate | hasApproximateGeographicRegion |
P185319
|
FINISHED |
| Object | northern Portugal |
—
|
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: northern Portugal | Statement: [Viana do Castelo station, hasApproximateGeographicRegion, northern Portugal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateGeographicRegion Context triple: [Viana do Castelo station, hasApproximateGeographicRegion, northern Portugal]
-
A.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
B.
hasGeographicalLocation
chosen
Indicates that an entity is situated in, or associated with, a specific geographical place or area.
-
C.
isGeographicallySpecific
Indicates that something is limited to or uniquely associated with a particular geographic location or area.
-
D.
geographicContext
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
-
E.
containsGeographicalArea
Indicates that one geographical area spatially encompasses or includes another geographical area within its boundaries.
- 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_69f76daeb6e48190a4c9a6b0edc80f72 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: May 3, 2026, 3:59 p.m.