Triple

T18262580
Position Surface form Disambiguated ID Type / Status
Subject Université de Lorraine E437398 entity
Predicate abbreviation P43 FINISHED
Object UL
UL is the commonly used abbreviation for Université de Lorraine, a French public university known for its wide range of academic and research programs.
 E1314855 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: UL | Statement: [Université de Lorraine, abbreviation, UL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UL
Context triple: [Université de Lorraine, abbreviation, UL]
  • A. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • B. UL
    UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
  • C. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • D. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • E. LU
    LU is the official vehicle registration code used on license plates for the Swiss canton of Lucerne.
  • 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: UL
Triple: [Université de Lorraine, abbreviation, UL]
Generated description
UL is the commonly used abbreviation for Université de Lorraine, a French public university known for its wide range of academic and research programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UL
Target entity description: UL is the commonly used abbreviation for Université de Lorraine, a French public university known for its wide range of academic and research programs.
  • A. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • B. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • C. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • D. UL
    UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
  • E. LU
    LU is the official vehicle registration code used on license plates for the Swiss canton of Lucerne.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff77882c81909774aefc57ccca3e completed April 19, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03b3f4a9e08190814c8fc05bf28d26 completed May 12, 2026, 11:12 p.m.
NEDg Description generation batch_6a03b4748aa48190a69855ba8e9563dd completed May 12, 2026, 11:15 p.m.
NED2 Entity disambiguation (via description) batch_6a03b4f794148190b01d310db48c2d6e completed May 12, 2026, 11:17 p.m.
Created at: April 10, 2026, 10:34 a.m.