Triple
T12777461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Kirwan |
E305413
|
entity |
| Predicate | wasKnightedFor |
P106856
|
FINISHED |
| Object | services to mental health and 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: services to mental health and rugby | Statement: [John Kirwan, wasKnightedFor, services to mental health and rugby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasKnightedFor Context triple: [John Kirwan, wasKnightedFor, services to mental health and rugby]
-
A.
wasKnightedAt
Indicates that a knighthood was formally conferred upon someone at a specific place or event.
-
B.
wasKnightedOn
Indicates that an entity received a knighthood on a specific date or occasion.
-
C.
confersKnighthood
Indicates that one entity formally grants the status or title of knighthood to another entity.
-
D.
isOrderOfKnighthood
Indicates that an entity is a formal chivalric or knightly order to which individuals can be admitted.
-
E.
appointedKnightOfTheGarter
Indicates that an entity has been formally appointed as a Knight of the Order of the Garter.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e595e008190b42dff3012d17d66 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:29 p.m.