Triple

T1026643
Position Surface form Disambiguated ID Type / Status
Subject Steve Case E22153 entity
Predicate familyName P18 FINISHED
Object Case
Case is a common English surname borne by various notable individuals across fields such as business, politics, and the arts.
 E119944 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: Case | Statement: [Steve Case, familyName, Case]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Case
Context triple: [Steve Case, familyName, Case]
  • A. Case Blue
    Case Blue was the German Wehrmacht’s 1942 summer offensive on the Eastern Front aimed at seizing the oil-rich Caucasus and advancing toward Stalingrad during World War II.
  • B. Case Yellow
    Case Yellow was the codename for Nazi Germany’s 1940 military campaign that rapidly conquered France and the Low Countries during World War II.
  • C. CASA
    CASA (Construcciones Aeronáuticas S.A.) was a Spanish aircraft manufacturer that became a key predecessor to Airbus through mergers in the European aerospace industry.
  • D. COUR
    COUR is the stock ticker symbol for Coursera, a major online learning platform offering courses, certificates, and degrees from universities and companies worldwide.
  • E. CASS
    CASS is the Cargo Accounts Settlement System, a global IATA-managed platform that streamlines and standardizes financial transactions between airlines and freight forwarders.
  • 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: Case
Triple: [Steve Case, familyName, Case]
Generated description
Case is a common English surname borne by various notable individuals across fields such as business, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Case
Target entity description: Case is a common English surname borne by various notable individuals across fields such as business, politics, and the arts.
  • A. Case Blue
    Case Blue was the German Wehrmacht’s 1942 summer offensive on the Eastern Front aimed at seizing the oil-rich Caucasus and advancing toward Stalingrad during World War II.
  • B. Case Yellow
    Case Yellow was the codename for Nazi Germany’s 1940 military campaign that rapidly conquered France and the Low Countries during World War II.
  • C. CASA
    CASA (Construcciones Aeronáuticas S.A.) was a Spanish aircraft manufacturer that became a key predecessor to Airbus through mergers in the European aerospace industry.
  • D. COUR
    COUR is the stock ticker symbol for Coursera, a major online learning platform offering courses, certificates, and degrees from universities and companies worldwide.
  • E. CASS
    CASS is the Cargo Accounts Settlement System, a global IATA-managed platform that streamlines and standardizes financial transactions between airlines and freight forwarders.
  • 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_69a493d6e380819097b384986ffc315c completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7f5e7b48190b26524573c2824ba completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bba40f88190b80010a837dfb1cc completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3c7d16748190a95aaffd04a867b3 completed March 7, 2026, 2:55 p.m.
NED2 Entity disambiguation (via description) batch_69ac3ce827b88190a5de06c695ad4ecb completed March 7, 2026, 2:57 p.m.
Created at: March 1, 2026, 7:41 p.m.