Triple
T11298298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juwan Howard |
E267509
|
entity |
| Predicate | playedWith |
P7956
|
FINISHED |
| Object | Yao Ming |
E105373
|
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: Yao Ming | Statement: [Juwan Howard, playedWith, Yao Ming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yao Ming Context triple: [Juwan Howard, playedWith, Yao Ming]
-
A.
Yao Ming
chosen
Yao Ming is a retired Chinese basketball center and Hall of Famer who became an NBA superstar with the Houston Rockets and helped globalize the sport.
-
B.
Li Ne
Li Ne is the daughter of former Chinese paramount leader Li Xiannian and the sister of retired Chinese tennis star Li Na.
-
C.
Yi Jianlian
Yi Jianlian is a Chinese professional basketball player known for his successful career in the Chinese Basketball Association and his tenure in the NBA.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
Michael Jordan
Michael Jordan is a legendary American basketball player widely regarded as one of the greatest athletes in the history of the sport.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a3616c8190a8fd23ca67463806 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a3e26e88190991127a5993a32a4 |
completed | April 19, 2026, 5 p.m. |
Created at: April 8, 2026, 9:32 p.m.