Triple
T9573663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biathlon at the 2002 Winter Olympics |
E230988
|
entity |
| Predicate | typeOfSkiing |
P89882
|
FINISHED |
| Object | cross-country skiing |
—
|
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: cross-country skiing | Statement: [Biathlon at the 2002 Winter Olympics, typeOfSkiing, cross-country skiing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSkiing Context triple: [Biathlon at the 2002 Winter Olympics, typeOfSkiing, cross-country skiing]
-
A.
skiAreaType
Indicates the specific type or classification of a ski area associated with an entity (e.g., resort, backcountry, terrain park).
-
B.
hasNightSkiing
Indicates that a location or facility offers skiing activities that take place during nighttime under artificial lighting.
-
C.
hasSkiLiftType
Indicates the specific type or category of ski lift associated with an entity.
-
D.
hasTreeLineSkiing
Indicates that a location or ski area offers skiing routes that pass through or alongside a line of trees.
-
E.
skiAreaName
Indicates that an entity has a specific name used to identify a ski area.
- F. None of above. chosen
Provenance (4 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99a94c788190a4bb5d2b676908ac |
completed | April 1, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:05 p.m.