Triple

T970334
Position Surface form Disambiguated ID Type / Status
Subject Money Heist E20929 entity
Predicate leadCharacter P1668 FINISHED
Object The Professor
The Professor is the mastermind strategist and enigmatic leader who orchestrates the meticulously planned heists in the Spanish series "Money Heist."
 E114999 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: The Professor | Statement: [Money Heist, leadCharacter, The Professor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Professor
Context triple: [Money Heist, leadCharacter, The Professor]
  • A. Gardner
    Gardner is a common English surname borne by numerous notable individuals across fields such as literature, science, and the arts.
  • B. Degory Priest
    Degory Priest was an English Pilgrim and early settler of Plymouth Colony who traveled on the Mayflower and participated in the founding governance of the colony.
  • C. Mr. Man
    "Mr. Man" is a song by Alicia Keys from her debut studio album "Songs in A Minor."
  • D. Elias Loomis
    Elias Loomis was a 19th-century American mathematician and physicist known for his work in astronomy, meteorology, and mathematical education.
  • E. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • 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: The Professor
Triple: [Money Heist, leadCharacter, The Professor]
Generated description
The Professor is the mastermind strategist and enigmatic leader who orchestrates the meticulously planned heists in the Spanish series "Money Heist."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The Professor
Target entity description: The Professor is the mastermind strategist and enigmatic leader who orchestrates the meticulously planned heists in the Spanish series "Money Heist."
  • A. Gardner
    Gardner is a common English surname borne by numerous notable individuals across fields such as literature, science, and the arts.
  • B. Degory Priest
    Degory Priest was an English Pilgrim and early settler of Plymouth Colony who traveled on the Mayflower and participated in the founding governance of the colony.
  • C. Mr. Man
    "Mr. Man" is a song by Alicia Keys from her debut studio album "Songs in A Minor."
  • D. Elias Loomis
    Elias Loomis was a 19th-century American mathematician and physicist known for his work in astronomy, meteorology, and mathematical education.
  • E. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4497d688190b59c3a195e377080 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1707339081909c69c7c613eed383 completed March 7, 2026, 12:16 p.m.
NEDg Description generation batch_69ac1841a6188190bca3ab98eb169d47 completed March 7, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_69ac18afee148190ac7431327588c31b completed March 7, 2026, 12:23 p.m.
Created at: March 1, 2026, 7:40 p.m.