Triple

T23484968
Position Surface form Disambiguated ID Type / Status
Subject Richard Dudman E570509 entity
Predicate hasChild P369 FINISHED
Object Martha Dudman
Martha Dudman is an American writer and memoirist known for works such as "Augusta, Gone," in which she chronicles her experiences raising a troubled teenage daughter.
E1768733 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: Martha Dudman | Statement: [Richard Dudman, hasChild, Martha Dudman]
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: Martha Dudman
Triple: [Richard Dudman, hasChild, Martha Dudman]
Generated description
Martha Dudman is an American writer and memoirist known for works such as "Augusta, Gone," in which she chronicles her experiences raising a troubled teenage daughter.

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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a752c678819087e5c50b8cf87d3d completed April 29, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7a1e53081908e89c77a8231a5e6 completed May 24, 2026, 7:24 a.m.
NEDg Description generation batch_6a12a81054a0819082a8d81a803e9d5c completed May 24, 2026, 7:26 a.m.
NED2 Entity disambiguation (via description) batch_6a12a84e1fc88190b93efc6dd11de7bd completed May 24, 2026, 7:27 a.m.
Created at: April 17, 2026, 6:03 p.m.