Triple
T16620035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Angles ski resort |
E403799
|
entity |
| Predicate | hasBeginnerArea |
P43109
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Les Angles ski resort, hasBeginnerArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeginnerArea Context triple: [Les Angles ski resort, hasBeginnerArea, yes]
-
A.
hasBeginnerTerrain
chosen
Indicates that something provides or includes terrain or areas suitable for beginners.
-
B.
hasStartingArea
Indicates that an entity is associated with, or begins from, a specific initial area or region.
-
C.
hasBeginnerFriendlyTraining
Indicates that an entity provides training or instructional resources suitable for beginners or those with little prior experience.
-
D.
hasWalkthroughArea
Indicates that one entity includes or provides a designated area intended for walking through or passing along.
-
E.
hasAmateurLevel
Indicates that an entity possesses an amateur level of skill, experience, or proficiency in a given activity or domain.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754c934c8190a0a8ddd747681aa7 |
completed | April 18, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.