Triple

T35715184
Position Surface form Disambiguated ID Type / Status
Subject Kyain Seikgyi E1031983 entity
Predicate locatedInAdministrativeTerritory P40 FINISHED
Object Kyain Seikgyi Township
Kyain Seikgyi Township is an administrative township in Kayin State, southeastern Myanmar, known for its rural communities and location near the Thai border.
E2153806 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: Kyain Seikgyi Township | Statement: [Kyain Seikgyi, locatedInAdministrativeTerritory, Kyain Seikgyi Township]
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: Kyain Seikgyi Township
Triple: [Kyain Seikgyi, locatedInAdministrativeTerritory, Kyain Seikgyi Township]
Generated description
Kyain Seikgyi Township is an administrative township in Kayin State, southeastern Myanmar, known for its rural communities and location near the Thai border.

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_69f76e0df1d08190965b1c6dff94c391 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a0f81030819094f90ac28322f8d7 completed May 3, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d1410c88190879bc299b0c0595a completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387e310da08190bf04f895f599d47f completed June 22, 2026, 12:13 a.m.
NED2 Entity disambiguation (via description) batch_6a387ebe432c8190848a35a2695d2204 completed June 22, 2026, 12:15 a.m.
Created at: May 3, 2026, 4:05 p.m.