Triple

T24122629
Position Surface form Disambiguated ID Type / Status
Subject Illinois's 10th congressional district E597702 entity
Predicate previouslyRepresentedBy P45113 FINISHED
Object Robert Dold
Robert Dold is an American politician and businessman who served as a Republican U.S. Representative from Illinois’s northern suburbs.
E1701878 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: Robert Dold | Statement: [Illinois's 10th congressional district, previouslyRepresentedBy, Robert Dold]
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: Robert Dold
Triple: [Illinois's 10th congressional district, previouslyRepresentedBy, Robert Dold]
Generated description
Robert Dold is an American politician and businessman who served as a Republican U.S. Representative from Illinois’s northern suburbs.

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_69e288c74200819098ab875b592cb39f completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dee5937c819092396751c23553ca completed April 29, 2026, 10:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec75c29c8190a214a4fcc5358010 completed May 22, 2026, 11:53 p.m.
NEDg Description generation batch_6a10ee8e2a008190962a88ee42e3c741 completed May 23, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_6a10f02156908190aa1fb061ae251f82 completed May 23, 2026, 12:09 a.m.
Created at: April 17, 2026, 11:05 p.m.