Triple

T14124137
Position Surface form Disambiguated ID Type / Status
Subject Erzurum Technical University E339981 entity
Predicate abbreviation P43 FINISHED
Object ETU
ETU is the commonly used abbreviation for Erzurum Technical University, a public higher education institution located in Erzurum, Turkey.
 E1082538 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: ETU | Statement: [Erzurum Technical University, abbreviation, ETU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ETU
Context triple: [Erzurum Technical University, abbreviation, ETU]
  • A. ETOU
    ETOU is the ICAO airport code for Wiesbaden Army Airfield, a U.S. military airbase located near Wiesbaden, Germany.
  • B. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • C. ETI
    ETI is the station code for Estación Etiopía, a metro station in Mexico City’s rapid transit system.
  • D. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • E. ERTA
    ERTA is a landmark 1981 U.S. federal law that significantly reduced individual and business income taxes to stimulate economic growth during the Reagan administration.
  • 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: ETU
Triple: [Erzurum Technical University, abbreviation, ETU]
Generated description
ETU is the commonly used abbreviation for Erzurum Technical University, a public higher education institution located in Erzurum, Turkey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ETU
Target entity description: ETU is the commonly used abbreviation for Erzurum Technical University, a public higher education institution located in Erzurum, Turkey.
  • A. ETOU
    ETOU is the ICAO airport code for Wiesbaden Army Airfield, a U.S. military airbase located near Wiesbaden, Germany.
  • B. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • C. ETI
    ETI is the station code for Estación Etiopía, a metro station in Mexico City’s rapid transit system.
  • D. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • E. ERTA
    ERTA is a landmark 1981 U.S. federal law that significantly reduced individual and business income taxes to stimulate economic growth during the Reagan administration.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6095548881908a9e66adccca92d2 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf0a7a7c8190860d8ce47b5f0732 completed May 7, 2026, 6:50 p.m.
NEDg Description generation batch_69fce0dec2488190be9c24d3744e7243 completed May 7, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69fce206b0588190a0f4b24231d3c365 completed May 7, 2026, 7:03 p.m.
Created at: April 9, 2026, 10:22 p.m.