Triple

T9741567
Position Surface form Disambiguated ID Type / Status
Subject Pixels E236196 entity
Predicate featuresFictionalCharacter P50141 FINISHED
Object Pac-Man E367894 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: Pac-Man | Statement: [Pixels, featuresFictionalCharacter, Pac-Man]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pac-Man
Context triple: [Pixels, featuresFictionalCharacter, Pac-Man]
  • A. Pac-Man chosen
    Pac-Man is a classic arcade video game character created by Namco, known for navigating mazes while eating pellets and avoiding ghosts.
  • B. Pac-Man
    Pac-Man is the ring nickname of Filipino boxing legend Manny Pacquiao, reflecting his aggressive, relentless fighting style.
  • C. Pacman
    Pacman is a lightweight, command-line package manager originally developed for Arch Linux, known for its speed and simple binary package handling.
  • D. Pong
    Pong is a comic ministerial character in Giacomo Puccini’s opera "Turandot," serving alongside Ping and Pang to provide both humor and commentary on the unfolding drama.
  • E. Pong
    Pong is one of the earliest and most influential arcade video games, a simple two-dimensional table tennis simulation that helped launch the commercial video game industry.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f2af3e48190b83a442cd0e84062 completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1aff2339c8190b164b13b54a40cec completed April 5, 2026, 12:42 a.m.
Created at: March 30, 2026, 8:23 p.m.