Triple

T4313020
Position Surface form Disambiguated ID Type / Status
Subject Atlanta E94117 entity
Predicate follows P134 FINISHED
Object Marthasville E16951 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: Marthasville | Statement: [Atlanta, follows, Marthasville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marthasville
Context triple: [Atlanta, follows, Marthasville]
  • A. Marthasville chosen
    Marthasville was the former name of the city now known as Atlanta, Georgia, during its early 19th-century development as a railroad terminus.
  • B. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • C. Slatersville
    Slatersville is a historic village in North Smithfield, Rhode Island, known as one of America’s first planned mill villages centered around early textile manufacturing.
  • D. Luthersville
    Luthersville is a small rural city in Meriwether County, Georgia, known for its quiet residential character and location in west-central Georgia.
  • E. Markleeville
    Markleeville is a small unincorporated community in the Sierra Nevada of California known for its historic charm, outdoor recreation, and role as the administrative center of Alpine County.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350d8bff88190bcf7dd419d5f4312 completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d07e7a288190b1fcd0075d14cd11 completed March 14, 2026, 9:17 p.m.
Created at: March 12, 2026, 11:12 p.m.