Triple

T4425451
Position Surface form Disambiguated ID Type / Status
Subject Overture Services E95196 entity
Predicate poweredSearchFor P23063 FINISHED
Object Lycos E96745 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: Lycos | Statement: [Overture Services, poweredSearchFor, Lycos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lycos
Context triple: [Overture Services, poweredSearchFor, Lycos]
  • A. Lycos chosen
    Lycos is an early web search engine and internet portal that was popular in the 1990s alongside rivals like AltaVista and Yahoo.
  • B. Infoseek
    Infoseek was an early web search engine and internet portal that gained prominence in the mid-1990s before being acquired and integrated into Disney’s online properties.
  • C. AltaVista
    AltaVista was one of the earliest and most popular web search engines of the 1990s, known for its fast, comprehensive internet search before being eclipsed by later competitors.
  • D. Alexa Internet
    Alexa Internet was a web traffic analysis and ranking company best known for providing website popularity metrics and analytics services before its shutdown in 2022.
  • E. AOL
    AOL is a pioneering American internet and online services company best known for popularizing dial-up access and email in the 1990s and early 2000s.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35640269c8190a88fc6b59070561b completed March 13, 2026, 12:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f633a69c8190b062c2a78b0f8319 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:30 p.m.