Triple
T31008416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doug Howlett |
E790137
|
entity |
| Predicate | clubNumberOfTriesForMunster |
P171117
|
FINISHED |
| Object | over 35 in all competitions |
—
|
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 35 in all competitions | Statement: [Doug Howlett, clubNumberOfTriesForMunster, over 35 in all competitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clubNumberOfTriesForMunster Context triple: [Doug Howlett, clubNumberOfTriesForMunster, over 35 in all competitions]
-
A.
clubDebutForMunster
Indicates that an entity made their first official club appearance specifically for the Munster team.
-
B.
numberOfMunsterSeniorHurlingMedals
Indicates the quantity of Munster Senior Hurling Championship medals that an entity has won.
-
C.
clubDebutForUlster
Indicates that an entity made their first club appearance specifically for the Ulster team.
-
D.
EuropeanChampionshipAppearances
Indicates the number of times an entity has participated in a European Championship tournament.
-
E.
clubAppearances
Indicates the number of official matches a player has played for a particular club.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f698ad83a08190a6834056ccc3e3a4 |
completed | May 3, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f697e92e2c8190bed50d5ba0981b64 |
completed | May 3, 2026, 12:33 a.m. |
Created at: April 29, 2026, 8:57 p.m.