Triple

T9611748
Position Surface form Disambiguated ID Type / Status
Subject TOPS-20 E232117 entity
Predicate basedOn P98 FINISHED
Object TENEX E431123 NE FINISHED

How this triple was built (2 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: TENEX | Statement: [TOPS-20, basedOn, TENEX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TENEX
Context triple: [TOPS-20, basedOn, TENEX]
  • A. TENEX operating system chosen
    TENEX operating system is an early time-sharing operating system for the PDP-10 that introduced advanced virtual memory and interactive computing features influential in later systems.
  • B. Ten Ten
    "Ten Ten" is a popular Nigerian Afrobeats song performed by the Mo' Hits All Stars collective.
  • C. TX-10
    TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
  • D. Tenix Defence
    Tenix Defence was a major Australian defence contractor known for constructing naval vessels and providing maritime and military engineering services.
  • E. Teldec
    Teldec was a prominent German classical music record label known for its high-quality recordings and influential catalog of orchestral and early music.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a87764481909ab96cd2ab96d14b completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d179513f9081909bcd9a456c640ba3 completed April 4, 2026, 8:49 p.m.
Created at: March 30, 2026, 8:09 p.m.