Triple

T16750868
Position Surface form Disambiguated ID Type / Status
Subject Damascus, Georgia E407071 entity
Predicate hasOfficialName P66 FINISHED
Object Damascus, Georgia E407071 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: Damascus, Georgia | Statement: [Damascus, Georgia, hasOfficialName, Damascus, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damascus, Georgia
Context triple: [Damascus, Georgia, hasOfficialName, Damascus, Georgia]
  • A. Damascus, Georgia chosen
    Damascus, Georgia is a small rural town located in southwestern Georgia within Early County.
  • B. Bethlehem, Georgia
    Bethlehem, Georgia is a small town in northeastern Georgia known for its Christmas-themed name and seasonal postmark that attracts holiday mail from across the country.
  • C. Dublin, Georgia
    Dublin, Georgia is a small city in Laurens County known as a regional hub in central Georgia with a historic downtown and annual St. Patrick’s Festival.
  • D. Fairmount, Georgia
    Fairmount, Georgia is a small rural city in northwestern Georgia known for its quiet community and proximity to the foothills of the Appalachian Mountains.
  • E. Cairo, Georgia
    Cairo, Georgia is a small city in the southwestern part of the state known for its agricultural economy and historic downtown.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa271de48190b4a535408aeef734 completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a522255c8190ab16d7ad233fcd3b completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:21 a.m.