Triple
T31661019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid Canterbury Rugby Football Union |
E807999
|
entity |
| Predicate | hasAgeGrade |
P110301
|
FINISHED |
| Object | senior rugby |
—
|
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: senior rugby | Statement: [Mid Canterbury Rugby Football Union, hasAgeGrade, senior rugby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeGrade Context triple: [Mid Canterbury Rugby Football Union, hasAgeGrade, senior rugby]
-
A.
hasAgeClassification
chosen
Indicates that an entity is associated with a specific age-based category or grouping.
-
B.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
hasAgeGuidelines
Indicates that there are specified age-related rules or recommendations governing how something should be accessed, used, or engaged with.
-
D.
intendedForAgeGroup
Indicates that something is designed, suitable, or targeted for use by a specific age group.
-
E.
hasLowerAge
Indicates that one entity is younger in age than another entity.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 10:57 p.m.