Triple

T18935
Position Surface form Disambiguated ID Type / Status
Subject University of Göttingen E374 entity
Predicate shortName P43 FINISHED
Object GAU
GAU is an abbreviation commonly used for the University of Göttingen, a major research university in Göttingen, Germany.
 E1298 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: GAU | Statement: [University of Göttingen, shortName, GAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GAU
Context triple: [University of Göttingen, shortName, GAU]
  • A. HUP
    HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
  • B. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • C. ATE
    ATE is a U.S. National Science Foundation program that supports the education and training of technicians for advanced technology fields through partnerships between two-year colleges, industry, and other educational institutions.
  • D. Blitz
    The Blitz was the sustained German bombing campaign against the United Kingdom, particularly London, during 1940–1941 in World War II.
  • E. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • 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: GAU
Triple: [University of Göttingen, shortName, GAU]
Generated description
GAU is an abbreviation commonly used for the University of Göttingen, a major research university in Göttingen, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GAU
Target entity description: GAU is an abbreviation commonly used for the University of Göttingen, a major research university in Göttingen, Germany.
  • A. HUP
    HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
  • B. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • C. ATE
    ATE is a U.S. National Science Foundation program that supports the education and training of technicians for advanced technology fields through partnerships between two-year colleges, industry, and other educational institutions.
  • D. Blitz
    The Blitz was the sustained German bombing campaign against the United Kingdom, particularly London, during 1940–1941 in World War II.
  • E. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • 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_69a240778d288190815c0052ebbbcc91 completed Feb. 28, 2026, 1:10 a.m.
NER Named-entity recognition batch_69a2465d9038819087f875a5afac9541 completed Feb. 28, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69a248e73c6c8190a83d10709aa3f9c7 completed Feb. 28, 2026, 1:46 a.m.
NEDg Description generation batch_69a249cbc63881908a99d2f82270b96b completed Feb. 28, 2026, 1:50 a.m.
NED2 Entity disambiguation (via description) batch_69a24a54686c819088cfe99468b2c693 completed Feb. 28, 2026, 1:52 a.m.
Created at: Feb. 28, 2026, 1:14 a.m.