Triple
T17505355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheng Wei |
E426299
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Didi Dache |
—
|
NE NERFINISHED |
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 Dache | Statement: [Cheng Wei, founded, Didi Dache]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Didi Dache Context triple: [Cheng Wei, founded, Didi Dache]
-
A.
Didi Dache
chosen
Didi Dache was a pioneering Chinese taxi-hailing mobile app that later became part of the ride-hailing giant Didi Chuxing.
-
B.
Didi
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.
-
C.
Didi Petet
Didi Petet was a prominent Indonesian actor and comedian best known for his roles in popular films and television series from the 1980s and 1990s.
-
D.
Dida
Dida is a Brazilian former professional goalkeeper best known for his time at AC Milan, where he was regarded as one of the world’s top keepers in the early 2000s.
-
E.
Didi Ortley
Didi Ortley is a character portrayed by Niecy Nash in the dark comedy television series "Scream Queens."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452159c28819084b2cba4313ddf28 |
completed | April 19, 2026, 3:55 a.m. |
Created at: April 10, 2026, 5:48 a.m.