Triple

T7714545
Position Surface form Disambiguated ID Type / Status
Subject Kung Fu Panda 2 E174847 entity
Predicate villain P4675 FINISHED
Object Lord Shen E683354 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: Lord Shen | Statement: [Kung Fu Panda 2, villain, Lord Shen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lord Shen
Context triple: [Kung Fu Panda 2, villain, Lord Shen]
  • A. Lord Shen chosen
    Lord Shen is the main peacock antagonist in Kung Fu Panda 2, a ruthless and power-obsessed warlord who seeks to conquer China using deadly fireworks-based weaponry.
  • B. Lord Shang
    Lord Shang was an influential Chinese statesman and legalist reformer of the Warring States period, best known for transforming the state of Qin into a highly centralized and powerful military state.
  • C. Chi-Fu
    Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
  • D. Shizong
    Shizong is the temple name of the Jiajing Emperor, a Ming dynasty ruler known for his long reign and efforts to strengthen imperial authority and Confucian orthodoxy in China.
  • E. Dorohusk
    Dorohusk is a village in eastern Poland near the Ukrainian border, known as an important road and rail border crossing point between the two countries.
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ca8f048190a6ea27b8cee2f93e completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b508fa2081908ed05ca8c4815249 completed March 29, 2026, 5:13 a.m.
Created at: March 27, 2026, 4:04 p.m.