Triple
T3952668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Euro 2016 Final |
E84901
|
entity |
| Predicate | decidingGoalScorer |
P2220
|
FINISHED |
| Object |
Éder
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.
|
E402562
|
NE FINISHED |
How this triple was built (4 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 Final, decidingGoalScorer, Éder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Éder Context triple: [UEFA Euro 2016 Final, decidingGoalScorer, Éder]
-
A.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
B.
Diego Pol
Diego Pol is an Argentine paleontologist renowned for his work on South American dinosaurs and the discovery of several significant sauropod species.
-
C.
Rubén
Rubén is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
D.
Estévez
Estévez is the original Spanish family name of actor Martin Sheen, also shared by several of his children in the entertainment industry.
-
E.
Adalberto
Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Éder Triple: [UEFA Euro 2016 Final, decidingGoalScorer, Éder]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Éder Target entity description: 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.
-
A.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
B.
Diego Pol
Diego Pol is an Argentine paleontologist renowned for his work on South American dinosaurs and the discovery of several significant sauropod species.
-
C.
Rubén
Rubén is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
D.
Estévez
Estévez is the original Spanish family name of actor Martin Sheen, also shared by several of his children in the entertainment industry.
-
E.
Adalberto
Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
- F. None of above. chosen
Provenance (5 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef939d1308190930dc2c8272eafa4 |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533a80d4c8190bb1aac1b2900d9a8 |
completed | March 14, 2026, 10:08 a.m. |
| NEDg | Description generation | batch_69b5341fb74081909a33753e5fdd5c32 |
completed | March 14, 2026, 10:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b534d279548190bee44aea7828ed3b |
completed | March 14, 2026, 10:13 a.m. |
Created at: March 9, 2026, 3:30 p.m.