Triple

T8130152
Position Surface form Disambiguated ID Type / Status
Subject Red Shift E189832 entity
Predicate settingLocation P40 FINISHED
Object Chester E640330 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: Chester | Statement: [Red Shift, settingLocation, Chester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chester
Context triple: [Red Shift, settingLocation, Chester]
  • A. Chester
    Chester is the given name of Chester W. Nimitz, the prominent U.S. Navy fleet admiral who played a leading role in the Pacific theater during World War II.
  • B. Chester
    Chester is a small, historically industrial city in southeastern Pennsylvania that lies just southwest of Philadelphia along the Delaware River.
  • C. Chester chosen
    Chester is a historic walled city in northwest England known for its Roman heritage, medieval architecture, and distinctive two-tiered shopping galleries called the Rows.
  • D. Chester
    Chester is a historic walled city in northwest England renowned for its Roman heritage, medieval architecture, and well-preserved city walls.
  • E. Chester
    Chester is a historic walled city in northwest England, renowned for its well-preserved Roman and medieval architecture.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43b6b4dc8190be237e6dd21c863b completed March 31, 2026, 3:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc947a7354819088c6f3cc6ab677cf completed April 1, 2026, 3:43 a.m.
Created at: March 30, 2026, 5:34 p.m.