Triple

T9002971
Position Surface form Disambiguated ID Type / Status
Subject OS X Mountain Lion E215078 entity
Predicate includedFeature P1393 FINISHED
Object Gatekeeper E41427 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: Gatekeeper | Statement: [OS X Mountain Lion, includedFeature, Gatekeeper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gatekeeper
Context triple: [OS X Mountain Lion, includedFeature, Gatekeeper]
  • A. Gatekeeper chosen
    Gatekeeper is a macOS security feature that helps protect users by allowing only trusted software to run on the system.
  • B. Gatekeeper
    "Gatekeeper" is a powerful song by Jessie Reyez that confronts sexual harassment and exploitation in the music industry.
  • C. The Gatekeeper
    The Gatekeeper is the stage name of a member of Gravediggaz, the influential horrorcore hip hop group known for its dark, horror-themed lyrics and production.
  • D. GateKeeper
    GateKeeper is a steel wing roller coaster at Cedar Point in Ohio, renowned for its record-breaking inversions and dramatic keyhole elements, designed by Swiss manufacturer Bolliger & Mabillard.
  • E. The Gate
    The Gate is a 1987 supernatural horror film about children who accidentally unleash demonic forces from a mysterious hole in their backyard.
  • 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_69ca83a12d648190b1e4fe11e8a31890 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6957bd5481908ce74f32f8d197de completed April 1, 2026, 12:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0e0a28c81909b6d2c6cd80e24d4 completed April 3, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:05 p.m.