Triple
T6077873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Euro 2016 |
E135446
|
entity |
| Predicate | winningGoalScorerInFinal |
P2695
|
FINISHED |
| Object | Éder |
E402562
|
NE 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: Éder | Statement: [UEFA Euro 2016, winningGoalScorerInFinal, Éder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Éder Context triple: [UEFA Euro 2016, winningGoalScorerInFinal, Éder]
-
A.
Éder
chosen
Éder is a Portuguese footballer best known for scoring the extra-time winning goal that secured Portugal’s first major international trophy at UEFA Euro 2016.
-
B.
Eder
The Eder is a river in central Germany that flows through the state of Hesse before joining the Fulda River.
-
C.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
D.
Diego Pol
Diego Pol is an Argentine paleontologist renowned for his work on South American dinosaurs and the discovery of several significant sauropod species.
-
E.
Rubén
Rubén is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057706d9881909b52093282593886 |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d48f0508190991453dc17c53b89 |
completed | March 23, 2026, 11 a.m. |
Created at: March 22, 2026, 4:11 p.m.