Triple

T22723099
Position Surface form Disambiguated ID Type / Status
Subject German Center for Lung Research E561916 entity
Predicate abbreviation P43 FINISHED
Object DZL
DZL is a German research network dedicated to advancing the understanding, prevention, and treatment of lung diseases through collaborative, translational research.
 E1550677 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: DZL | Statement: [German Center for Lung Research, abbreviation, DZL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DZL
Context triple: [German Center for Lung Research, abbreviation, DZL]
  • A. SZL
    SZL is the ISO 4217 currency code for the Swazi lilangeni, the official currency of Eswatini.
  • B. SZL
    SZL is the IATA airport code for Whiteman Air Force Base, a United States Air Force installation in Missouri.
  • C. DZG
    DZG is the vehicle registration code assigned to cars registered in the Bogatynia area of Poland.
  • D. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • E. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • 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: DZL
Triple: [German Center for Lung Research, abbreviation, DZL]
Generated description
DZL is a German research network dedicated to advancing the understanding, prevention, and treatment of lung diseases through collaborative, translational research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DZL
Target entity description: DZL is a German research network dedicated to advancing the understanding, prevention, and treatment of lung diseases through collaborative, translational research.
  • A. SZL
    SZL is the ISO 4217 currency code for the Swazi lilangeni, the official currency of Eswatini.
  • B. SZL
    SZL is the IATA airport code for Whiteman Air Force Base, a United States Air Force installation in Missouri.
  • C. DZG
    DZG is the vehicle registration code assigned to cars registered in the Bogatynia area of Poland.
  • D. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • E. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17927e0348190a4dba430563ef155 completed April 29, 2026, 3:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b7ee34d6c8190b731cd64b3acd6f1 completed May 18, 2026, 9:04 p.m.
NEDg Description generation batch_6a0b7f4f748481909f87c6fb2a5aa913 completed May 18, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_6a0b7faf97fc8190b978f223db313541 completed May 18, 2026, 9:07 p.m.
Created at: April 17, 2026, 3:20 p.m.