Triple
T15456214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Crunch |
E371774
|
entity |
| Predicate | hasMatchFrequency |
P18808
|
FINISHED |
| Object | at least once per Six Nations season |
—
|
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: at least once per Six Nations season | Statement: [Le Crunch, hasMatchFrequency, at least once per Six Nations season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMatchFrequency Context triple: [Le Crunch, hasMatchFrequency, at least once per Six Nations season]
-
A.
hasFrequencyCategory
Indicates that something is associated with a particular classification of how often it occurs or is used.
-
B.
hasFrequencyNote
chosen
Indicates that something is associated with a specific note describing how often it occurs or is repeated.
-
C.
hasMatchFormat
Indicates that something (such as a game, event, or competition) is conducted according to a specified match format or structure.
-
D.
hasLowerFrequencyIn
Indicates that one entity occurs or appears less frequently within a specified context than another entity.
-
E.
matchupFrequency
Indicates how often a particular pair or set of entities are matched or paired against each other within a given context or timeframe.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f146a2c8190882741af3ec15268 |
completed | April 16, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:31 a.m.