Triple

T20352087
Position Surface form Disambiguated ID Type / Status
Subject Sendhil Mullainathan E496036 entity
Predicate coAuthor P398 FINISHED
Object Markus Mobius
Markus Möbius is an economist known for his research in behavioral and experimental economics, often collaborating on influential empirical studies.
 E1425101 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: Markus Mobius | Statement: [Sendhil Mullainathan, coAuthor, Markus Mobius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Markus Mobius
Context triple: [Sendhil Mullainathan, coAuthor, Markus Mobius]
  • A. Markus
    Markus is the given first name of the renowned abstract expressionist painter Mark Rothko.
  • B. Markus
    Markus is a masculine given name of Latin origin, commonly used in various European countries and derived from the name Marcus.
  • C. Markus
    Markus is the first name of American professional baseball star Mookie Betts.
  • D. Markus Lilienthal
    Markus Lilienthal is a person notable for bearing the surname Lilienthal, though specific widely known biographical details about him are not well documented.
  • E. John Markus
    John Markus is an American television writer and producer best known for his work on sitcoms such as The Cosby Show and for creating the series Kristin.
  • 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: Markus Mobius
Triple: [Sendhil Mullainathan, coAuthor, Markus Mobius]
Generated description
Markus Möbius is an economist known for his research in behavioral and experimental economics, often collaborating on influential empirical studies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Markus Mobius
Target entity description: Markus Möbius is an economist known for his research in behavioral and experimental economics, often collaborating on influential empirical studies.
  • A. Markus
    Markus is the given first name of the renowned abstract expressionist painter Mark Rothko.
  • B. Markus
    Markus is a masculine given name of Latin origin, commonly used in various European countries and derived from the name Marcus.
  • C. Markus
    Markus is the first name of American professional baseball star Mookie Betts.
  • D. Markus Lilienthal
    Markus Lilienthal is a person notable for bearing the surname Lilienthal, though specific widely known biographical details about him are not well documented.
  • E. John Markus
    John Markus is an American television writer and producer best known for his work on sitcoms such as The Cosby Show and for creating the series Kristin.
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67850ace48190b19aff5780fef7e8 completed April 20, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a086967aef88190b138be722f410e82 completed May 16, 2026, 12:56 p.m.
NEDg Description generation batch_6a0869f7b4208190858fdeae882e008d completed May 16, 2026, 12:58 p.m.
NED2 Entity disambiguation (via description) batch_6a086a893f1c81909bc40e3c4db0e147 completed May 16, 2026, 1 p.m.
Created at: April 16, 2026, 11:25 a.m.