Triple
T2649915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1970 FIFA World Cup |
E53871
|
entity |
| Predicate | featuredPlayer |
P2630
|
FINISHED |
| Object |
Gérson
Gérson is a legendary Brazilian midfielder renowned for orchestrating play in Brazil’s iconic 1970 FIFA World Cup–winning team.
|
E291063
|
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: Gérson | Statement: [1970 FIFA World Cup, featuredPlayer, Gérson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gérson Context triple: [1970 FIFA World Cup, featuredPlayer, Gérson]
-
A.
Gilles
Gilles is a masculine given name of French origin, commonly used as a variant of the name Gil or Giles.
-
B.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
C.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
D.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
-
E.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
- 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: Gérson Triple: [1970 FIFA World Cup, featuredPlayer, Gérson]
Generated description
Gérson is a legendary Brazilian midfielder renowned for orchestrating play in Brazil’s iconic 1970 FIFA World Cup–winning team.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gérson Target entity description: Gérson is a legendary Brazilian midfielder renowned for orchestrating play in Brazil’s iconic 1970 FIFA World Cup–winning team.
-
A.
Gilles
Gilles is a masculine given name of French origin, commonly used as a variant of the name Gil or Giles.
-
B.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
C.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
D.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
-
E.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd91ca1288190ba302b04bac4c153 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf49dc7c8190bebc1c75f6d00ef9 |
completed | March 10, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69afafddb2a081909b891eed7ba5411d |
completed | March 10, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb10304488190a1129efae36b3c4e |
completed | March 10, 2026, 5:49 a.m. |
Created at: March 6, 2026, 9:53 p.m.