Triple
T8006808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Quan |
E186382
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sun |
E675695
|
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: Sun | Statement: [Sun Quan, familyName, Sun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sun Context triple: [Sun Quan, familyName, Sun]
-
A.
Sun
chosen
Sun I-hsien is a Taiwanese politician who has served in various governmental roles, including as a legislator.
-
B.
Sun
The Sun is the massive, luminous star at the center of our solar system that provides the light and heat necessary for life on Earth.
-
C.
The Sun
The Sun is a British tabloid newspaper known for its sensationalist journalism, celebrity gossip, and large circulation.
-
D.
The Sun
The Sun is a vibrant, monumental painting by Norwegian artist Edvard Munch that depicts a radiant, dominating sun over a coastal landscape, symbolizing life, energy, and renewal.
-
E.
SUN
SUN is the National Rail station code for Sunderland railway station in Tyne and Wear, England.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf8a6048190970685a83fd2f59d |
completed | March 31, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe12c068c8190a6ea7e924a7748c6 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:18 p.m.