Triple

T5712250
Position Surface form Disambiguated ID Type / Status
Subject Dani Rodrik E125935 entity
Predicate givenName P17 FINISHED
Object Dani
Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
 E541652 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: Dani | Statement: [Dani Rodrik, givenName, Dani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dani
Context triple: [Dani Rodrik, givenName, Dani]
  • A. Dani
    Dani is a fictional character played by actress Adria Arjona, known from her role in the fantasy-romance film "Emerald City" and other screen appearances.
  • B. Dan
    Dan is a biblical figure recognized as one of the twelve sons of Jacob and the traditional ancestor of the Tribe of Dan in the Hebrew Bible.
  • C. Dan
    Dan is a character in the play "Clybourne Park," representing a contemporary figure who uncovers the neighborhood’s buried history and helps connect past events to present-day tensions.
  • D. Dan
    Dan is the protagonist of Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," a post-scarcity future resident of a reputation-based society centered around a Disney theme park.
  • E. Dan
    Dan is a male given name commonly used in English-speaking countries, often as a short form of Daniel.
  • 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: Dani
Triple: [Dani Rodrik, givenName, Dani]
Generated description
Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dani
Target entity description: Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
  • A. Dani
    Dani is a fictional character played by actress Adria Arjona, known from her role in the fantasy-romance film "Emerald City" and other screen appearances.
  • B. Dan
    Dan is a biblical figure recognized as one of the twelve sons of Jacob and the traditional ancestor of the Tribe of Dan in the Hebrew Bible.
  • C. Dan
    Dan is a character in the play "Clybourne Park," representing a contemporary figure who uncovers the neighborhood’s buried history and helps connect past events to present-day tensions.
  • D. Dan
    Dan is the protagonist of Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," a post-scarcity future resident of a reputation-based society centered around a Disney theme park.
  • E. Dan
    Dan is a male given name commonly used in English-speaking countries, often as a short form of Daniel.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024b386a08190bd2738d93861edc2 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a72181081909209a38c3ff7460b completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05cd2dea88190bc79ca0a7709e7ca completed March 22, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_69c05d8c85f88190a1a962794eeecd8d completed March 22, 2026, 9:22 p.m.
Created at: March 22, 2026, 3:46 p.m.