Triple

T5791309
Position Surface form Disambiguated ID Type / Status
Subject Aged in Wood E128399 entity
Predicate hasFictionalCharacter P15645 FINISHED
Object Max Fabian
Max Fabian is a fictional character from the 1950 film "Aged in Wood."
E553673 NE FINISHED

How this triple was built (4 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: Max Fabian | Statement: [Aged in Wood, hasFictionalCharacter, Max Fabian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Fabian
Context triple: [Aged in Wood, hasFictionalCharacter, Max Fabian]
  • A. Dietrich Hrabak
    Dietrich Hrabak was a German Luftwaffe fighter ace and high-ranking officer during World War II, known for his leadership roles on the Eastern Front.
  • B. Felix Steiner
    Felix Steiner was a high-ranking German SS commander during World War II who led several Waffen-SS formations on the Eastern and Western Fronts.
  • C. Moritz Borman
    Moritz Borman is a film producer known for working on major Hollywood productions, including the science fiction action film "Terminator Salvation."
  • D. Emil Puhl
    Emil Puhl was a high-ranking German banker and vice president of the Reichsbank who played a key role in managing Nazi Germany’s looted assets and was later convicted as a war criminal.
  • E. Paul Tabori
    Paul Tabori was a Hungarian-British writer, journalist, and screenwriter known for his work in mid-20th-century film and literature, often exploring psychological and speculative themes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Max Fabian
Triple: [Aged in Wood, hasFictionalCharacter, Max Fabian]
Generated description
Max Fabian is a fictional character from the 1950 film "Aged in Wood."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Max Fabian
Target entity description: Max Fabian is a fictional character from the 1950 film "Aged in Wood."
  • A. Dietrich Hrabak
    Dietrich Hrabak was a German Luftwaffe fighter ace and high-ranking officer during World War II, known for his leadership roles on the Eastern Front.
  • B. Felix Steiner
    Felix Steiner was a high-ranking German SS commander during World War II who led several Waffen-SS formations on the Eastern and Western Fronts.
  • C. Moritz Borman
    Moritz Borman is a film producer known for working on major Hollywood productions, including the science fiction action film "Terminator Salvation."
  • D. Emil Puhl
    Emil Puhl was a high-ranking German banker and vice president of the Reichsbank who played a key role in managing Nazi Germany’s looted assets and was later convicted as a war criminal.
  • E. Paul Tabori
    Paul Tabori was a Hungarian-British writer, journalist, and screenwriter known for his work in mid-20th-century film and literature, often exploring psychological and speculative themes.
  • F. None of above. chosen

Provenance (5 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a56c73c81908a1c72c86e474b54 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0d71b7881909108c7347ce91317 completed March 23, 2026, 3:17 a.m.
NEDg Description generation batch_69c0b1cb731481909de9c3fde3595b7b completed March 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69c0b27f53608190b2a1f78e3cd1b634 completed March 23, 2026, 3:24 a.m.
Created at: March 22, 2026, 3:51 p.m.