Triple

T27351676
Position Surface form Disambiguated ID Type / Status
Subject Qi State History Museum E684374 entity
Predicate hasSubject P450 FINISHED
Object Qi royal family
The Qi royal family was the ruling house of the ancient Chinese state of Qi, a powerful feudal kingdom during the Zhou dynasty known for its political influence and cultural achievements.
E1766032 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: Qi royal family | Statement: [Qi State History Museum, hasSubject, Qi royal family]
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: Qi royal family
Triple: [Qi State History Museum, hasSubject, Qi royal family]
Generated description
The Qi royal family was the ruling house of the ancient Chinese state of Qi, a powerful feudal kingdom during the Zhou dynasty known for its political influence and cultural achievements.

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_69ef1480a76481908684256ddd5bfda3 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62ba8515881908899834ffc730a6e completed May 2, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129cce8ef481908b11972024839e0a completed May 24, 2026, 6:38 a.m.
NEDg Description generation batch_6a129dc607c48190981b49d79b0b1784 completed May 24, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_6a129e4151208190995590e78cf35502 completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:49 a.m.