Triple
T20639584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sainte-Anne |
E507183
|
entity |
| Predicate | waterSports |
P56827
|
FINISHED |
| Object | swimming |
—
|
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: swimming | Statement: [Sainte-Anne, waterSports, swimming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterSports Context triple: [Sainte-Anne, waterSports, swimming]
-
A.
waterSport
chosen
Indicates participation in or association with a sport or recreational activity that takes place on or in water.
-
B.
aquaticsDiscipline
Indicates that one entity is an aquatic sports discipline or category associated with another entity.
-
C.
hasWaterRelatedActivity
Indicates that an entity engages in, offers, or is associated with an activity involving water (e.g., swimming, boating, or other water-based actions).
-
D.
tookOnWater
Indicates that an entity began to fill or absorb water, typically in an unintended or problematic way (e.g., a vessel leaking or flooding).
-
E.
hasWaterActivity
Indicates that one entity possesses, exhibits, or is characterized by a particular level or type of water-related activity (such as moisture content, water availability, or water-based processes).
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad126b6481908d4e235bd73dda2e |
completed | April 20, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69e5a0155bd48190b3c769a12cc2c83d |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 16, 2026, 11:42 a.m.