Triple

T36649815
Position Surface form Disambiguated ID Type / Status
Subject Kathy King E904813 entity
Predicate hasSurname P18 FINISHED
Object King
King is a common English surname historically associated with people who worked in or near royal households or adopted the name as a symbolic title.
E1611 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: King | Statement: [Kathy King, hasSurname, King]
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: King
Triple: [Kathy King, hasSurname, King]
Generated description
King is a common English surname historically associated with people who worked in or near royal households or adopted the name as a symbolic title.

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_69f76e6d3a3c81909db73eda9e0516bd completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c73185e88190b3c55bf1408793f6 completed May 3, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a095da0fc81909f74bbe3a45e1702 completed June 23, 2026, 4:19 a.m.
NEDg Description generation batch_6a3a0bd0829481908176aef50415ae8a completed June 23, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a3a0c576c9081908e8b04ce32702faa completed June 23, 2026, 4:32 a.m.
Created at: May 3, 2026, 4:11 p.m.