Triple

T8384881
Position Surface form Disambiguated ID Type / Status
Subject Annie Montrose E197788 entity
Predicate associatedWith P37 FINISHED
Object Teddy Sanders E214683 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: Teddy Sanders | Statement: [Annie Montrose, associatedWith, Teddy Sanders]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teddy Sanders
Context triple: [Annie Montrose, associatedWith, Teddy Sanders]
  • A. Teddy Sanders chosen
    Teddy Sanders is the cautious yet politically minded NASA Administrator in Andy Weir’s science fiction novel (and its film adaptation) "The Martian."
  • B. Teddy Sanders
    Teddy Sanders is a fictional character from the comedy film "Neighbors," portrayed as the charismatic yet rowdy fraternity leader who clashes with his new neighbors.
  • C. Karl Pitterson
    Karl Pitterson is a Jamaican record producer and audio engineer best known for his work on classic reggae and dub recordings in the 1970s and 1980s.
  • D. Marshall Pease
    Marshall Pease is a computer scientist best known for co-authoring the seminal paper that introduced the Byzantine Generals Problem in distributed computing and fault tolerance.
  • E. Theodore Scott Glenn
    Theodore Scott Glenn is an American actor known for his intense, rugged performances in films such as "The Right Stuff," "The Silence of the Lambs," and "Training Day."
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80e03eb08190a458c9caa0524e0f completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce3967fd108190b045ea1328b1dc4b completed April 2, 2026, 9:39 a.m.
Created at: March 30, 2026, 6:02 p.m.