Triple
T22780907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuo Fu |
E563832
|
entity |
| Predicate | associatedWithPhilosopher |
P1481
|
FINISHED |
| Object | Lie Yukou |
—
|
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: Lie Yukou | Statement: [Shuo Fu, associatedWithPhilosopher, Lie Yukou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lie Yukou Context triple: [Shuo Fu, associatedWithPhilosopher, Lie Yukou]
-
A.
Lie Yukou
chosen
Lie Yukou is an ancient Chinese philosopher traditionally credited with authoring the Daoist classic "Liezi," though his historical existence remains uncertain.
-
B.
Yuji
Yuji is a common Japanese masculine given name used by various real and fictional individuals.
-
C.
Yukie
Yukie is a Japanese film featuring Ken Watanabe in a prominent role.
-
D.
Kodama Yuta
Kodama Yuta is a Japanese individual notable for bearing the surname Kodama, though specific widely recognized public achievements or roles under this name are not well documented.
-
E.
Youki Kudoh
Youki Kudoh is a Japanese actress and singer known internationally for her roles in films such as "Mystery Train," "Heaven's Burning," and "Snow Falling on Cedars."
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c2cab0881908df1d0629b43d350 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 3:28 p.m.