Triple

T9566877
Position Surface form Disambiguated ID Type / Status
Subject CCS E230808 entity
Predicate influenced P9 FINISHED
Object LOTOS
LOTOS is a formal specification language for describing and analyzing the behavior of distributed and concurrent systems, particularly in communication protocols.
 E807612 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: LOTOS | Statement: [CCS, influenced, LOTOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LOTOS
Context triple: [CCS, influenced, LOTOS]
  • A. Lotso
    Lotso is the strawberry-scented teddy bear who serves as the main antagonist in Pixar's animated film Toy Story 3.
  • B. LOTG
    LOTG is the standard abbreviation for the Laws of the Game, the official rulebook that governs how association football (soccer) is played worldwide.
  • C. LOT
    LOT is the national flag carrier airline of Poland, headquartered in Warsaw and operating an extensive network of domestic and international flights.
  • D. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • E. Lott
    Lott is the surname of English singer and actress Pixie Lott, known for her pop hits and work in film and television.
  • 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: LOTOS
Triple: [CCS, influenced, LOTOS]
Generated description
LOTOS is a formal specification language for describing and analyzing the behavior of distributed and concurrent systems, particularly in communication protocols.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LOTOS
Target entity description: LOTOS is a formal specification language for describing and analyzing the behavior of distributed and concurrent systems, particularly in communication protocols.
  • A. Lotso
    Lotso is the strawberry-scented teddy bear who serves as the main antagonist in Pixar's animated film Toy Story 3.
  • B. LOTG
    LOTG is the standard abbreviation for the Laws of the Game, the official rulebook that governs how association football (soccer) is played worldwide.
  • C. LOT
    LOT is the national flag carrier airline of Poland, headquartered in Warsaw and operating an extensive network of domestic and international flights.
  • D. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • E. Lott
    Lott is the surname of English singer and actress Pixie Lott, known for her pop hits and work in film and television.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd996df4f08190b19bbaefb10a9789 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d152b09c808190aff32419f2cbb15f completed April 4, 2026, 6:04 p.m.
NEDg Description generation batch_69d153d59844819086a0f50e6a7624b2 completed April 4, 2026, 6:09 p.m.
NED2 Entity disambiguation (via description) batch_69d1546a503c81908edc9588adabc172 completed April 4, 2026, 6:11 p.m.
Created at: March 30, 2026, 8:04 p.m.