Triple

T8508930
Position Surface form Disambiguated ID Type / Status
Subject Alexandra Exter E201403 entity
Predicate workLocation P7 FINISHED
Object Odessa E38290 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: Odessa | Statement: [Alexandra Exter, workLocation, Odessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odessa
Context triple: [Alexandra Exter, workLocation, Odessa]
  • A. Odessa
    Odessa is a mid-sized city in western Texas known for its oil industry, high school football culture, and role in the Permian Basin energy region.
  • B. Odessa
    Odessa is a central, devoutly religious housekeeper in James Baldwin’s play "The Amen Corner," known for her loyalty and moral grounding amid the story’s family and church conflicts.
  • C. Odesa chosen
    Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
  • D. Kherson
    Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
  • E. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5df74e8819086b1445cc907e371 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1399616708190968442c5389166cf completed April 4, 2026, 4:17 p.m.
Created at: March 30, 2026, 6:15 p.m.