Triple

T8389923
Position Surface form Disambiguated ID Type / Status
Subject Mike Flanagan E197914 entity
Predicate directorOf P537 FINISHED
Object Oculus E730770 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: Oculus | Statement: [Mike Flanagan, directorOf, Oculus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oculus
Context triple: [Mike Flanagan, directorOf, Oculus]
  • A. Oculus chosen
    Oculus is a 2013 psychological horror film written and directed by Mike Flanagan that centers on a haunted mirror and the traumatic effects it has on a family.
  • B. Oculus
    The Oculus is a striking, winged transportation hub and shopping center in Lower Manhattan designed by architect Santiago Calatrava, serving as the main transit hall for the rebuilt World Trade Center site.
  • C. Oculus VR
    Oculus VR is a virtual reality technology company best known for developing the Oculus Rift headset and helping popularize modern consumer VR experiences.
  • D. Oculus Rift
    Oculus Rift is a virtual reality headset developed by Oculus VR that enables immersive 3D gaming and interactive experiences on PC.
  • E. Oculus Go
    Oculus Go is a standalone virtual reality headset designed for untethered, mobile VR experiences without the need for a PC or smartphone.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb810ac380819095bd67f0555ac2a8 completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02cb3a1481908d30993d47c70039 completed April 2, 2026, 5:46 a.m.
Created at: March 30, 2026, 6:03 p.m.