Triple
T7875786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HC Davos |
E182846
|
entity |
| Predicate | tournamentFrequency |
P65013
|
FINISHED |
| Object | annual Spengler Cup |
—
|
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: annual Spengler Cup | Statement: [HC Davos, tournamentFrequency, annual Spengler Cup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tournamentFrequency Context triple: [HC Davos, tournamentFrequency, annual Spengler Cup]
-
A.
gamesFrequency
Indicates how often the related entities engage in playing games together or participate in game-related activities.
-
B.
frequencyOfTournament
chosen
Indicates how often a particular tournament takes place within a given time period.
-
C.
meetingFrequency
Indicates how often a meeting or recurring gathering takes place over a given period.
-
D.
matchupFrequency
Indicates how often a particular pair or set of entities are matched or paired against each other within a given context or timeframe.
-
E.
broadcastFrequency
Indicates the specific radio or transmission frequency at which a broadcast is sent or received.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39aa7ca88190b88a18f6a8971e51 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:57 p.m.