Triple
T5232930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Analects |
E118151
|
entity |
| Predicate | hasKeyFigure |
P810
|
FINISHED |
| Object | Zigong |
E211982
|
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: Zigong | Statement: [Analects, hasKeyFigure, Zigong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zigong Context triple: [Analects, hasKeyFigure, Zigong]
-
A.
Zigong
chosen
Zigong is a historic industrial city in southern Sichuan, China, best known for its ancient salt industry and renowned dinosaur fossil sites.
-
B.
Zengzi
Zengzi was a prominent disciple of Confucius, renowned for his moral integrity and influential role in the development and transmission of Confucian thought.
-
C.
Yan Hui
Yan Hui was Confucius’s favorite disciple, renowned for his exceptional virtue, humility, and understanding of Confucian teachings.
-
D.
Zhu Houxi
Zhu Houxi was a Ming dynasty imperial prince, known primarily as a son of the Hongzhi Emperor of China.
-
E.
Junzi
Junzi is a central Confucian ideal of the morally exemplary "gentleman" or noble person who embodies virtue, righteousness, and proper conduct.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0389048190b55b7c44fe657044 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe604a848190a3f6cc90185b3ca2 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:49 p.m.