Triple

T27795558
Position Surface form Disambiguated ID Type / Status
Subject Samuel C. Pomeroy E701198 entity
Predicate name P16 FINISHED
Object Samuel Clarke Pomeroy
Samuel Clarke Pomeroy was a 19th-century American politician and abolitionist who served as one of the first U.S. senators from Kansas during and after the Civil War.
E1907276 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: Samuel Clarke Pomeroy | Statement: [Samuel C. Pomeroy, name, Samuel Clarke Pomeroy]
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: Samuel Clarke Pomeroy
Triple: [Samuel C. Pomeroy, name, Samuel Clarke Pomeroy]
Generated description
Samuel Clarke Pomeroy was a 19th-century American politician and abolitionist who served as one of the first U.S. senators from Kansas during and after the Civil War.

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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6380a86648190b4ef3ee0ce498b12 completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ecc2800819090b2bc6e61264e04 completed June 9, 2026, 1:39 a.m.
NEDg Description generation batch_6a276febe8e48190a61b0e20ac44ab06 completed June 9, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a27708bfc588190abd7fa5039f5153a completed June 9, 2026, 1:46 a.m.
Created at: April 27, 2026, 5:31 p.m.