Triple

T23759784
Position Surface form Disambiguated ID Type / Status
Subject Duke Huan of Qi E587217 entity
Predicate predecessor P97 FINISHED
Object Duke Xi of Qi
Duke Xi of Qi was an early Spring and Autumn period ruler of the ancient Chinese state of Qi, known primarily as the father and predecessor of the powerful hegemon Duke Huan of Qi.
E1634387 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: Duke Xi of Qi | Statement: [Duke Huan of Qi, predecessor, Duke Xi of Qi]
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: Duke Xi of Qi
Triple: [Duke Huan of Qi, predecessor, Duke Xi of Qi]
Generated description
Duke Xi of Qi was an early Spring and Autumn period ruler of the ancient Chinese state of Qi, known primarily as the father and predecessor of the powerful hegemon Duke Huan of Qi.

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_69e2490b8ac48190a6b35f1d5500486b completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bdb1d6348190afb3f0fbea1b9ca3 completed April 29, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe33338488190b625688937f4a7a9 completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe44e2f9c8190a16f81052341c70a completed May 22, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe4e5d698819092a5d1b75f213ca0 completed May 22, 2026, 5:08 a.m.
Created at: April 17, 2026, 7:14 p.m.