Triple
T33426697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biellese area |
E856002
|
entity |
| Predicate | hasSportActivity |
P971
|
FINISHED |
| Object | hiking |
—
|
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: hiking | Statement: [Biellese area, hasSportActivity, hiking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSportActivity Context triple: [Biellese area, hasSportActivity, hiking]
-
A.
hasLocalSport
Indicates that a place or community is associated with, supports, or regularly engages in a particular sport at the local level.
-
B.
hasHumanActivities
Indicates that certain human actions, behaviors, or practices are present, performed, or associated with a given entity.
-
C.
hasAthleticLevel
Indicates the degree or category of athletic ability, fitness, or performance associated with an entity.
-
D.
hasAthletics
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
E.
hasRecreationActivity
chosen
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
- 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: May 1, 2026, 1:36 a.m.