Triple

T6020477
Position Surface form Disambiguated ID Type / Status
Subject Fars E134049 entity
Predicate majorCity P316 FINISHED
Object Lar
Lar is a historic city in Iran’s Fars Province, known for its traditional architecture and role as a regional commercial center.
E562224 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: Lar | Statement: [Fars, majorCity, Lar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lar
Context triple: [Fars, majorCity, Lar]
  • A. Larrelt
    Larrelt is a district of the German seaport city of Emden in Lower Saxony.
  • B. Lari
    Lari is a regional dialect of the Sindhi language spoken primarily in parts of Sindh, Pakistan.
  • C. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • D. Lai
    Lai is a variant spelling of the Chinese surname Li, commonly found in Chinese-speaking communities and their diasporas.
  • E. Laur
    Laur is a rural municipality in the province of Nueva Ecija in the Philippines, known for its agricultural landscape and proximity to the Sierra Madre mountain range.
  • 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: Lar
Triple: [Fars, majorCity, Lar]
Generated description
Lar is a historic city in Iran’s Fars Province, known for its traditional architecture and role as a regional commercial center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lar
Target entity description: Lar is a historic city in Iran’s Fars Province, known for its traditional architecture and role as a regional commercial center.
  • A. Larrelt
    Larrelt is a district of the German seaport city of Emden in Lower Saxony.
  • B. Lari
    Lari is a regional dialect of the Sindhi language spoken primarily in parts of Sindh, Pakistan.
  • C. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • D. Lai
    Lai is a variant spelling of the Chinese surname Li, commonly found in Chinese-speaking communities and their diasporas.
  • E. Laur
    Laur is a rural municipality in the province of Nueva Ecija in the Philippines, known for its agricultural landscape and proximity to the Sierra Madre mountain range.
  • 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_69c008742a5c8190b9cb9c2787a3d8b3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04fba86a48190984e95d5adf7c7f1 completed March 22, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108be2170819084b4b940e52b0185 completed March 23, 2026, 9:32 a.m.
NEDg Description generation batch_69c10abc9aa08190acf1ced6a8be322e completed March 23, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_69c10b5c118c8190aaf5461c40472022 completed March 23, 2026, 9:43 a.m.
Created at: March 22, 2026, 4:07 p.m.