Triple

T29797005
Position Surface form Disambiguated ID Type / Status
Subject Marquis Wen of Wei E756580 entity
Predicate precededBy P97 FINISHED
Object Marquis Wu of Wei
Marquis Wu of Wei was an early ruler of the State of Wei during China’s Warring States period, known primarily as the predecessor of the influential Marquis Wen of Wei.
E1888564 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: Marquis Wu of Wei | Statement: [Marquis Wen of Wei, precededBy, Marquis Wu of Wei]
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: Marquis Wu of Wei
Triple: [Marquis Wen of Wei, precededBy, Marquis Wu of Wei]
Generated description
Marquis Wu of Wei was an early ruler of the State of Wei during China’s Warring States period, known primarily as the predecessor of the influential Marquis Wen of Wei.

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_69f22454583081908927516cb9938d1d completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f674e7548c81909acffee32ca126f9 completed May 2, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1b96d5c8190b7b1a9892229862a completed June 8, 2026, 4:45 p.m.
NEDg Description generation batch_6a26f2a076d4819086a7a4bf85946196 completed June 8, 2026, 4:49 p.m.
NED2 Entity disambiguation (via description) batch_6a26f34f9b488190b90e3e36cf7174dc completed June 8, 2026, 4:52 p.m.
Created at: April 29, 2026, 5:16 p.m.