Triple

T1870043
Position Surface form Disambiguated ID Type / Status
Subject Commodore Amiga 500 E39012 entity
Predicate alsoKnownAs P39 FINISHED
Object A500
A500 is the common shorthand for the Commodore Amiga 500, a popular late-1980s home computer known for its advanced graphics and sound capabilities.
 E208099 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: A500 | Statement: [Commodore Amiga 500, alsoKnownAs, A500]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: A500
Context triple: [Commodore Amiga 500, alsoKnownAs, A500]
  • A. SA5
    SA5 is the 3GPP Service and System Aspects working group responsible for management, orchestration, and operations of mobile communication networks.
  • B. M55
    M55 is a New York City bus route that provides public transit service connecting to the Whitehall Terminal area in Lower Manhattan.
  • C. A40
    A40 is a major French motorway, also known as the "Autoroute Blanche," that connects Mâcon to the Mont Blanc region through the Jura and Alps.
  • D. A35
    A35 is a major French motorway in the Alsace region that runs north–south near the German border, connecting cities such as Strasbourg and Mulhouse.
  • E. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • 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: A500
Triple: [Commodore Amiga 500, alsoKnownAs, A500]
Generated description
A500 is the common shorthand for the Commodore Amiga 500, a popular late-1980s home computer known for its advanced graphics and sound capabilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: A500
Target entity description: A500 is the common shorthand for the Commodore Amiga 500, a popular late-1980s home computer known for its advanced graphics and sound capabilities.
  • A. SA5
    SA5 is the 3GPP Service and System Aspects working group responsible for management, orchestration, and operations of mobile communication networks.
  • B. M55
    M55 is a New York City bus route that provides public transit service connecting to the Whitehall Terminal area in Lower Manhattan.
  • C. A40
    A40 is a major French motorway, also known as the "Autoroute Blanche," that connects Mâcon to the Mont Blanc region through the Jura and Alps.
  • D. A35
    A35 is a major French motorway in the Alsace region that runs north–south near the German border, connecting cities such as Strasbourg and Mulhouse.
  • E. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0b95c0c8190a37907755541f8c6 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1dab2a481909adb0a3132348cee completed March 8, 2026, 7:45 p.m.
NEDg Description generation batch_69add25c9c208190a576cf1123c0a2e6 completed March 8, 2026, 7:47 p.m.
NED2 Entity disambiguation (via description) batch_69add32c32b08190be6624eefa2fa386 completed March 8, 2026, 7:51 p.m.
Created at: March 4, 2026, 7:34 p.m.