Triple

T16315992
Position Surface form Disambiguated ID Type / Status
Subject Fox Mulder E396173 entity
Predicate partner P1136 FINISHED
Object Dana Scully E396174 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: Dana Scully | Statement: [Fox Mulder, partner, Dana Scully]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dana Scully
Context triple: [Fox Mulder, partner, Dana Scully]
  • A. Dana Scully chosen
    Dana Scully is a skeptical FBI agent and medical doctor who investigates paranormal cases alongside Fox Mulder in the science fiction television series The X-Files.
  • B. Scully
    Scully is a surname most famously associated with Vin Scully, the legendary American sportscaster known for his long tenure as the voice of the Los Angeles Dodgers.
  • C. Scully
    Scully is the Irish-American hotel proprietor in Stephen Crane’s short story “The Blue Hotel,” known for his attempts to maintain order among his volatile guests.
  • D. Kay Scarpetta
    Kay Scarpetta is a fictional medical examiner and crime-solver who stars as the protagonist in Patricia Cornwell’s popular forensic crime novel series.
  • E. Claire Temple
    Claire Temple is a compassionate and resourceful nurse in the Marvel universe who frequently aids street-level heroes like Daredevil and Luke Cage, often serving as a crucial moral and medical support.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e296b1e9988190a1dce9f1ed7031df completed April 17, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001fa9f6dc81908e6cbb4e340356e1 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:06 a.m.