Triple
T9774542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Blacks–France rugby rivalry |
E237213
|
entity |
| Predicate | totalMatchesApproximate |
P12965
|
FINISHED |
| Object | over 60 test matches |
—
|
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: over 60 test matches | Statement: [All Blacks–France rugby rivalry, totalMatchesApproximate, over 60 test matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalMatchesApproximate Context triple: [All Blacks–France rugby rivalry, totalMatchesApproximate, over 60 test matches]
-
A.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
-
B.
matchOf
Indicates that one entity is a specific match, counterpart, or corresponding instance of another entity within a defined context or set.
-
C.
matchupFrequency
chosen
Indicates how often a particular pair or set of entities are matched or paired against each other within a given context or timeframe.
-
D.
numberOfGamesInMatch
Indicates the total count of individual games that make up a single match.
-
E.
holdsApproximatelyFor
Indicates that a condition, relation, or value is valid only to an approximate degree or within a tolerance, rather than holding exactly.
- 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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13148288190bcbb3b4a066d9fc1 |
completed | April 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69cd03d3b68c81909e570401a891b9f2 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:26 p.m.