Triple

T1091726
Position Surface form Disambiguated ID Type / Status
Subject Technical University of Munich E24177 entity
Predicate memberOf P10 FINISHED
Object TU9
TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
E126174 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: TU9 | Statement: [Technical University of Munich, memberOf, TU9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TU9
Context triple: [Technical University of Munich, memberOf, TU9]
  • A. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • B. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • C. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • D. TUNAIR
    TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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: TU9
Triple: [Technical University of Munich, memberOf, TU9]
Generated description
TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TU9
Target entity description: TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
  • A. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • B. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • C. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • D. TUNAIR
    TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b982018481908b222df095e318c0 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c2a20b48190b3a550f6e5ee13e1 completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4cae760881909329701561ad2ba6 completed March 7, 2026, 4:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac4d7176808190b74d535d7e1b7c6a completed March 7, 2026, 4:08 p.m.
Created at: March 1, 2026, 7:42 p.m.