Triple

T8865353
Position Surface form Disambiguated ID Type / Status
Subject Fatima Robinson E211004 entity
Predicate familyName P18 FINISHED
Object Robinson E75069 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: Robinson | Statement: [Fatima Robinson, familyName, Robinson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robinson
Context triple: [Fatima Robinson, familyName, Robinson]
  • A. Robinson chosen
    Robinson is a common English surname borne by numerous notable figures across politics, sports, arts, and other fields.
  • B. Crusoe Kurddal
    Crusoe Kurddal is an Indigenous Australian actor best known for his role in the acclaimed film "Ten Canoes."
  • C. Lewis D. Crusoe
    Lewis D. Crusoe was an influential American automotive executive and stylist who played a key role in shaping Ford’s postwar car designs, including the iconic Thunderbird.
  • D. Crusoe
    Crusoe is a family of low-power x86-compatible microprocessors developed by Transmeta, known for using code-morphing software to translate x86 instructions to a VLIW core.
  • E. Alexander Selkirk
    Alexander Selkirk was a Scottish sailor famously marooned on a Pacific island in the early 18th century, whose real-life survival story helped inspire Daniel Defoe’s novel "Robinson Crusoe."
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610569d08190b108107dfe397f18 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0d311148190823cc047e2908bc0 completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:51 p.m.