Triple

T11543867
Position Surface form Disambiguated ID Type / Status
Subject Torchlight E273734 entity
Predicate gameEngine P26587 FINISHED
Object OGRE
OGRE (Object-Oriented Graphics Rendering Engine) is an open-source, scene-oriented 3D rendering engine widely used for real-time graphics in games and simulations.
 E932630 NE FINISHED

How this triple was built (4 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: OGRE | Statement: [Torchlight, gameEngine, OGRE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OGRE
Context triple: [Torchlight, gameEngine, OGRE]
  • A. OSG
    OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
  • B. ASK/Ogre
    ASK/Ogre is a Latvian ice hockey club known for competing in the country’s top leagues and developing notable players such as coach and former player Oleg Znarok.
  • C. Glew
    Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
  • D. Aurora Engine
    Aurora Engine is a role-playing game engine developed by BioWare, best known for powering classic titles like Neverwinter Nights.
  • E. OGS
    OGS is the commonly used abbreviation for the New York State Office of General Services, the state agency responsible for managing government facilities, procurement, and support services.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: OGRE
Triple: [Torchlight, gameEngine, OGRE]
Generated description
OGRE (Object-Oriented Graphics Rendering Engine) is an open-source, scene-oriented 3D rendering engine widely used for real-time graphics in games and simulations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OGRE
Target entity description: OGRE (Object-Oriented Graphics Rendering Engine) is an open-source, scene-oriented 3D rendering engine widely used for real-time graphics in games and simulations.
  • A. OSG
    OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
  • B. ASK/Ogre
    ASK/Ogre is a Latvian ice hockey club known for competing in the country’s top leagues and developing notable players such as coach and former player Oleg Znarok.
  • C. Glew
    Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
  • D. Aurora Engine
    Aurora Engine is a role-playing game engine developed by BioWare, best known for powering classic titles like Neverwinter Nights.
  • E. OGS
    OGS is the commonly used abbreviation for the New York State Office of General Services, the state agency responsible for managing government facilities, procurement, and support services.
  • F. None of above. chosen

Provenance (5 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d886e1d754819089f3b6be3404fa0b completed April 10, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e685cc855881908ea96d84c76e3a4d completed April 20, 2026, 8 p.m.
NEDg Description generation batch_69e68fd8dcf08190b9e0cc7f868cb6a0 completed April 20, 2026, 8:43 p.m.
NED2 Entity disambiguation (via description) batch_69e6c10910548190b863e6f4a9a81ac3 completed April 21, 2026, 12:12 a.m.
Created at: April 8, 2026, 9:37 p.m.