Triple

T9116037
Position Surface form Disambiguated ID Type / Status
Subject Westron E218720 entity
Predicate writingSystem P454 FINISHED
Object Tengwar
Tengwar is a fictional script created by J.R.R. Tolkien, most famously used to write various languages of Middle-earth such as Quenya, Sindarin, and Westron.
E778894 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: Tengwar | Statement: [Westron, writingSystem, Tengwar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tengwar
Context triple: [Westron, writingSystem, Tengwar]
  • A. Aurebesh
    Aurebesh is the standardized writing system used to represent the Galactic Basic language in the Star Wars universe.
  • B. Sindarin
    Sindarin is an Elvish language created by J.R.R. Tolkien and widely spoken by characters in his Middle-earth legendarium.
  • C. Tigalari script
    The Tigalari script is a historical South Indian writing system used primarily to write Tulu and Sanskrit, closely related to other southern Brahmic scripts.
  • D. Tirhuta script
    Tirhuta script is a traditional Brahmic writing system historically used for the Maithili language of the Mithila region in India and Nepal.
  • E. Kawi script
    Kawi script is an ancient Brahmic-derived writing system historically used across Java and other parts of Southeast Asia to write Old Javanese and related languages.
  • 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: Tengwar
Triple: [Westron, writingSystem, Tengwar]
Generated description
Tengwar is a fictional script created by J.R.R. Tolkien, most famously used to write various languages of Middle-earth such as Quenya, Sindarin, and Westron.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tengwar
Target entity description: Tengwar is a fictional script created by J.R.R. Tolkien, most famously used to write various languages of Middle-earth such as Quenya, Sindarin, and Westron.
  • A. Aurebesh
    Aurebesh is the standardized writing system used to represent the Galactic Basic language in the Star Wars universe.
  • B. Sindarin
    Sindarin is an Elvish language created by J.R.R. Tolkien and widely spoken by characters in his Middle-earth legendarium.
  • C. Tigalari script
    The Tigalari script is a historical South Indian writing system used primarily to write Tulu and Sanskrit, closely related to other southern Brahmic scripts.
  • D. Tirhuta script
    Tirhuta script is a traditional Brahmic writing system historically used for the Maithili language of the Mithila region in India and Nepal.
  • E. Kawi script
    Kawi script is an ancient Brahmic-derived writing system historically used across Java and other parts of Southeast Asia to write Old Javanese and related languages.
  • 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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8a4c9e08190ba3603a5d00afb20 completed April 1, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0306837c0819099cd77925df0848d completed April 3, 2026, 9:26 p.m.
NEDg Description generation batch_69d032345f948190bdcb39b18b5f569d completed April 3, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69d032a9ee18819094931cfc13b8da32 completed April 3, 2026, 9:35 p.m.
Created at: March 30, 2026, 7:16 p.m.