Triple

T5687605
Position Surface form Disambiguated ID Type / Status
Subject Lontara script E125349 entity
Predicate ISO15924Code P208 FINISHED
Object Lont
Lont is the ISO 15924 four-letter code assigned to the Lontara script used for writing several languages of Sulawesi, Indonesia.
 E541747 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: Lont | Statement: [Lontara script, ISO15924Code, Lont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lont
Context triple: [Lontara script, ISO15924Code, Lont]
  • A. Lontzen
    Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
  • B. Luman
    Luman is a masculine given name of English origin, historically borne by figures such as the 19th-century American art patron Luman Reed.
  • C. Lorn
    Lorn is a historic district on the west coast of Scotland, known for its rugged landscapes and coastal scenery within the council area of Argyll and Bute.
  • D. Lorn
    Lorn is a residential suburb of Maitland in the Hunter Region of New South Wales, Australia, known for its historic homes and village-like atmosphere.
  • E. Lut
    Lut is a prophet in Islamic tradition, known for being sent to the people of Sodom and Gomorrah and warning them against their immoral behavior.
  • 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: Lont
Triple: [Lontara script, ISO15924Code, Lont]
Generated description
Lont is the ISO 15924 four-letter code assigned to the Lontara script used for writing several languages of Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lont
Target entity description: Lont is the ISO 15924 four-letter code assigned to the Lontara script used for writing several languages of Sulawesi, Indonesia.
  • A. Lontzen
    Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
  • B. Luman
    Luman is a masculine given name of English origin, historically borne by figures such as the 19th-century American art patron Luman Reed.
  • C. Lorn
    Lorn is a historic district on the west coast of Scotland, known for its rugged landscapes and coastal scenery within the council area of Argyll and Bute.
  • D. Lorn
    Lorn is a residential suburb of Maitland in the Hunter Region of New South Wales, Australia, known for its historic homes and village-like atmosphere.
  • E. Lut
    Lut is a prophet in Islamic tradition, known for being sent to the people of Sodom and Gomorrah and warning them against their immoral behavior.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023be18a081908c72fb5b0e1852f9 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a43cce88190b8ac801018f05561 completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05d24fdf481908cfa9c485cd9a9f3 completed March 22, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69c05dc3d3cc8190a6bb775b06136972 completed March 22, 2026, 9:23 p.m.
Created at: March 22, 2026, 3:44 p.m.