Triple
T16620021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Angles ski resort |
E403799
|
entity |
| Predicate | hasBlackRuns |
P44241
|
FINISHED |
| Object | expert slopes |
—
|
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: expert slopes | Statement: [Les Angles ski resort, hasBlackRuns, expert slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlackRuns Context triple: [Les Angles ski resort, hasBlackRuns, expert slopes]
-
A.
hasAllBlack
Indicates that the subject possesses or consists entirely of things that are black in color.
-
B.
hasBlackouts
Indicates that an entity experiences periods of complete or partial loss of consciousness, awareness, or memory.
-
C.
hasInrunLength
Indicates the length of the inrun portion (approach or run-up) associated with an activity, structure, or course.
-
D.
hasRace
Indicates that an entity possesses or is characterized by a particular race or racial classification.
-
E.
hasRunType
chosen
Indicates the type or category of a run associated with an entity (e.g., execution mode, run classification, or run configuration).
- 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.