Triple
T2430078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1958 FIFA World Cup |
E52820
|
entity |
| Predicate | BrazilKeyPlayer |
P39151
|
FINISHED |
| Object | Didi |
E216248
|
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: Didi | Statement: [1958 FIFA World Cup, BrazilKeyPlayer, Didi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Didi Context triple: [1958 FIFA World Cup, BrazilKeyPlayer, Didi]
-
A.
Didi
chosen
Didi was a legendary Brazilian attacking midfielder, renowned for his playmaking brilliance and key role in Brazil’s World Cup victories in 1958 and 1962.
-
B.
Kiko
Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
-
C.
Niña
Niña was one of the three ships in Christopher Columbus’s 1492 voyage across the Atlantic, notable for its role in the first European expedition to the Americas.
-
D.
Zaza
Zaza is an Iranian ethnic group primarily inhabiting eastern Turkey, known for speaking the Zazaki language and maintaining distinct cultural traditions.
-
E.
Lola
Lola is a fictional character portrayed by British actor Chiwetel Ejiofor.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd0d942048190bc5c715faa850632 |
completed | March 7, 2026, 7:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf6634a48190af82eab6b9750323 |
completed | March 9, 2026, 12:39 p.m. |
Created at: March 6, 2026, 9:43 p.m.