Triple

T27541216
Position Surface form Disambiguated ID Type / Status
Subject imperial court of Eastern Han E695239 entity
Predicate notableFigure P4290 FINISHED
Object Dou Wu
Dou Wu was a prominent Eastern Han dynasty official and scholar who played a key role in court politics before being executed during a power struggle with the eunuchs.
E1787778 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: Dou Wu | Statement: [imperial court of Eastern Han, notableFigure, Dou Wu]
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: Dou Wu
Triple: [imperial court of Eastern Han, notableFigure, Dou Wu]
Generated description
Dou Wu was a prominent Eastern Han dynasty official and scholar who played a key role in court politics before being executed during a power struggle with the eunuchs.

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_69ef5386c3e08190bfe33aa326e1f72b completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f5ddd908190b8ea190346ea26f1 completed May 2, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec9572088190ac23f7880c543644 completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed0fc060819085a0872a16a4badf completed May 24, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a12ed9d47988190a62268071859ede2 completed May 24, 2026, 12:22 p.m.
Created at: April 27, 2026, 1:31 p.m.