Triple
T28550647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Moir |
E722875
|
entity |
| Predicate | WorldChampionshipsMedalist |
P53100
|
FINISHED |
| Object | multiple years between 2008 and 2017 |
—
|
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: multiple years between 2008 and 2017 | Statement: [Scott Moir, WorldChampionshipsMedalist, multiple years between 2008 and 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldChampionshipsMedalist Context triple: [Scott Moir, WorldChampionshipsMedalist, multiple years between 2008 and 2017]
-
A.
WorldChampionshipMedalsTotal
Indicates the total number of medals an entity has won at world championship competitions.
-
B.
worldChampionshipsGoldMedal
Indicates that the subject has won a gold medal at a world championship competition.
-
C.
worldMedalist
chosen
Indicates that an entity has won a medal at a recognized world-level championship or world competition.
-
D.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
E.
olympicMedalist
Indicates that an entity has won at least one medal in an Olympic Games event.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 3:42 a.m.