Triple
T9573786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | speed skating at the 2002 Winter Olympics |
E230991
|
entity |
| Predicate | ovalType |
P89887
|
FINISHED |
| Object | indoor speed skating oval |
—
|
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: indoor speed skating oval | Statement: [speed skating at the 2002 Winter Olympics, ovalType, indoor speed skating oval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ovalType Context triple: [speed skating at the 2002 Winter Olympics, ovalType, indoor speed skating oval]
-
A.
oreType
Indicates the specific kind or classification of ore associated with an entity.
-
B.
outcomeType
Indicates the specific category or nature of the result produced by an event, process, or action.
-
C.
orderType
Indicates the specific category or classification of an order, such as its purpose, channel, or processing method.
-
D.
offeringType
Indicates the category or nature of what is being offered in a transaction or interaction (e.g., product, service, or other type of offering).
-
E.
eraType
Indicates the classification of a time period or era according to its type or category.
- 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.