Triple

T28324134
Position Surface form Disambiguated ID Type / Status
Subject War of the Eight Princes E717360 entity
Predicate opponent P437 FINISHED
Object Sima Yong
Sima Yong was a Jin dynasty prince and warlord who played a major role as one of the contending princes in the internecine War of the Eight Princes that devastated the Western Jin.
E1832503 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: Sima Yong | Statement: [War of the Eight Princes, opponent, Sima Yong]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sima Yong
Triple: [War of the Eight Princes, opponent, Sima Yong]
Generated description
Sima Yong was a Jin dynasty prince and warlord who played a major role as one of the contending princes in the internecine War of the Eight Princes that devastated the Western Jin.

Provenance (5 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_69eff6e6c3b08190ad78de6ba7f04548 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f6492ce1ec81908f51388ed8eea019 completed May 2, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a22cde8c8190b485074a904c686c completed June 6, 2026, 10:41 p.m.
NEDg Description generation batch_6a24a60b39cc819083b5bcabf6949022 completed June 6, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_6a24a9c8dfa481908396853b8d273d69 completed June 6, 2026, 11:14 p.m.
Created at: April 28, 2026, 12:26 a.m.