Triple
T8066028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgium national football team |
E188244
|
entity |
| Predicate | firstWorldCupAppearanceYear |
P66342
|
FINISHED |
| Object | 1930 |
—
|
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: 1930 | Statement: [Belgium national football team, firstWorldCupAppearanceYear, 1930]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWorldCupAppearanceYear Context triple: [Belgium national football team, firstWorldCupAppearanceYear, 1930]
-
A.
WorldCupDebutYear
chosen
Indicates the year in which an entity (typically a team or player) first participated in a World Cup tournament.
-
B.
worldCupAppearanceYear
Indicates the specific year in which an entity participated in a FIFA World Cup tournament.
-
C.
firstCricketWorldCupAppearance
Indicates the event or year in which an entity (typically a team or player) participated in a Cricket World Cup for the very first time.
-
D.
wasFirstWorldCupWith
Indicates that the referenced World Cup tournament was the first one to feature or include the specified characteristic, rule, format, or element.
-
E.
internationalTeamDebutYear
Indicates the year in which an entity (typically an athlete) first appeared in competition for an international team.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ff5547c8190a7ec5958a23e302f |
completed | March 31, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69cb049cd51c8190bb3b0f503e42fa8d |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:26 p.m.