Triple

T8665312
Position Surface form Disambiguated ID Type / Status
Subject Justus Liebig University Giessen E205656 entity
Predicate shortName P43 FINISHED
Object JLU
JLU is a public research university located in Giessen, Germany, known for its strong programs in the natural sciences, life sciences, and humanities.
 E749341 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: JLU | Statement: [Justus Liebig University Giessen, shortName, JLU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JLU
Context triple: [Justus Liebig University Giessen, shortName, JLU]
  • A. LJU
    LJU is the UN/LOCODE designation for Ljubljana Jože Pučnik Airport, the main international airport serving Ljubljana, Slovenia.
  • B. JL
    JL is the IATA airline designator used for Japan Airlines, the flag carrier of Japan.
  • C. JU
    JU is the commonly used abbreviation for Jiwaji University, a public university located in Gwalior, Madhya Pradesh, India.
  • D. JU
    JU is the station code for Jodhpur Junction, a major railway hub in the Indian state of Rajasthan.
  • E. JU
    JU is the two-letter IATA airline designator assigned to Air Serbia, the national flag carrier of Serbia.
  • 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: JLU
Triple: [Justus Liebig University Giessen, shortName, JLU]
Generated description
JLU is a public research university located in Giessen, Germany, known for its strong programs in the natural sciences, life sciences, and humanities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JLU
Target entity description: JLU is a public research university located in Giessen, Germany, known for its strong programs in the natural sciences, life sciences, and humanities.
  • A. LJU
    LJU is the UN/LOCODE designation for Ljubljana Jože Pučnik Airport, the main international airport serving Ljubljana, Slovenia.
  • B. JL
    JL is the IATA airline designator used for Japan Airlines, the flag carrier of Japan.
  • C. JU
    JU is the commonly used abbreviation for Jiwaji University, a public university located in Gwalior, Madhya Pradesh, India.
  • D. JU
    JU is the station code for Jodhpur Junction, a major railway hub in the Indian state of Rajasthan.
  • E. JU
    JU is the two-letter IATA airline designator assigned to Air Serbia, the national flag carrier of Serbia.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a0ae108190b33dadcc3cb18949 completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd1592788190a882fb7218f95807 completed April 2, 2026, 8:09 p.m.
NEDg Description generation batch_69cece8e5afc8190912b6eb9c80dd073 completed April 2, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_69cecf8ee4f48190bb901e35ade91b6c completed April 2, 2026, 8:20 p.m.
Created at: March 30, 2026, 6:30 p.m.