Triple

T22684456
Position Surface form Disambiguated ID Type / Status
Subject Boiler Room Girls E560871 entity
Predicate hasMember P10 FINISHED
Object Esther Newberg
Esther Newberg is an American literary agent and former political staffer best known as one of the “Boiler Room Girls” involved in the 1969 Chappaquiddick incident linked to Senator Ted Kennedy.
E1629130 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: Esther Newberg | Statement: [Boiler Room Girls, hasMember, Esther Newberg]
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: Esther Newberg
Triple: [Boiler Room Girls, hasMember, Esther Newberg]
Generated description
Esther Newberg is an American literary agent and former political staffer best known as one of the “Boiler Room Girls” involved in the 1969 Chappaquiddick incident linked to Senator Ted Kennedy.

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_69e2454d71b48190a1f80af9f82b6fcf completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17862c8a48190912a8ad09dfda795 completed April 29, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc985aba481908d88ba63e510b04c completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcb9821dc81909eda37ccba173c7c completed May 22, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcc2cd0108190a7531d50f6be2386 completed May 22, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:12 p.m.