Triple
T23282374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhao Tao |
E588899
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tao |
—
|
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: Tao | Statement: [Zhao Tao, givenName, Tao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tao Context triple: [Zhao Tao, givenName, Tao]
-
A.
Tao
Tao is a central antagonist character in the Sleeper universe, known for opposing the protagonist’s goals and driving much of the story’s conflict.
-
B.
Tao
chosen
Tao is a Chinese surname shared by numerous individuals, including the renowned mathematician Terence Tao.
-
C.
Tao
Tao is the central, ineffable principle in Chinese philosophy and religion, especially Taoism, representing the fundamental way or path underlying the universe and natural order.
-
D.
Tao
Tao is a key forensic specialist and detective on the crime drama series "Major Crimes," known for his analytical mind and methodical approach to investigations.
-
E.
Tao
Tao is a historical region in the South Caucasus, now largely in northeastern Turkey, that once formed part of the medieval Georgian principality of Tao-Klarjeti.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19643b8908190a2c29552b272dc61 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:58 p.m.