Triple

T647607
Position Surface form Disambiguated ID Type / Status
Subject Dr. Hermann Gottlieb E11275 entity
Predicate createdBy P806 FINISHED
Object Travis Beacham E30318 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: Travis Beacham | Statement: [Dr. Hermann Gottlieb, createdBy, Travis Beacham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travis Beacham
Context triple: [Dr. Hermann Gottlieb, createdBy, Travis Beacham]
  • A. Travis Beacham chosen
    Travis Beacham is an American screenwriter best known for co-writing the science fiction monster film "Pacific Rim."
  • B. Brian VanDeMark
    Brian VanDeMark is an American historian and author known for his work on U.S. foreign policy and the Vietnam War, including coauthoring influential studies of that conflict.
  • C. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • D. Nick Hendricks
    Nick Hendricks is a frustrated office worker from the dark comedy film "Horrible Bosses," who conspires with his friends to murder their abusive employers.
  • E. Shane Hurlbut
    Shane Hurlbut is an American cinematographer known for his work on major Hollywood films and his influential role in advancing digital cinematography techniques.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f1cb24481909d3b41a56b29dee9 completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd46422408190911e6eaec5866fe8 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:36 p.m.