Triple

T28324049
Position Surface form Disambiguated ID Type / Status
Subject Leigudun archaeological area E717358 entity
Predicate culture P1114 FINISHED
Object State of Zeng
The State of Zeng was an ancient Chinese polity of the Zhou dynasty era, known primarily from rich archaeological finds such as bronzes and tombs that reveal a distinctive regional culture.
 E1812858 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: State of Zeng | Statement: [Leigudun archaeological area, culture, State of Zeng]
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: State of Zeng
Triple: [Leigudun archaeological area, culture, State of Zeng]
Generated description
The State of Zeng was an ancient Chinese polity of the Zhou dynasty era, known primarily from rich archaeological finds such as bronzes and tombs that reveal a distinctive regional culture.

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_6a1627b152b48190bf7043eb598dd89a completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a16280d37f48190a67241e83ee869eb completed May 26, 2026, 11:09 p.m.
NED2 Entity disambiguation (via description) batch_6a16286f3c708190841c6dc41328de75 completed May 26, 2026, 11:10 p.m.
Created at: April 28, 2026, 12:26 a.m.