Triple
T2425208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grzegorz Lato |
E53509
|
entity |
| Predicate | numberOfGoalsForNationalTeam |
P9098
|
FINISHED |
| Object | 45 |
—
|
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: 45 | Statement: [Grzegorz Lato, numberOfGoalsForNationalTeam, 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsForNationalTeam Context triple: [Grzegorz Lato, numberOfGoalsForNationalTeam, 45]
-
A.
hasPlayedForNationalTeam
Indicates that an athlete has been a member of and appeared in competition for a specified national team.
-
B.
nationalTeamAppearances
Indicates the number of official matches in which an entity has represented its national team.
-
C.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
WorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup final tournaments.
-
E.
associatedWithNationalTeam
Indicates that an entity has a formal connection or involvement with a specific national team, such as playing for, coaching, or otherwise being officially linked to it.
- 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f342e88190a430b02842ded418 |
completed | March 7, 2026, 6:47 a.m. |
| PD | Predicate disambiguation | batch_69abc5a889948190b77de4ef6ac815a8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:42 p.m.