Triple

T38000994
Position Surface form Disambiguated ID Type / Status
Subject Palaw E948095 entity
Predicate partOf P40 FINISHED
Object Palaw Township
Palaw Township is an administrative township in Tanintharyi Region in southern Myanmar, known for its coastal location along the Andaman Sea and its largely rural, agriculture- and fishing-based communities.
E2252353 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: Palaw Township | Statement: [Palaw, partOf, Palaw 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: Palaw Township
Triple: [Palaw, partOf, Palaw Township]
Generated description
Palaw Township is an administrative township in Tanintharyi Region in southern Myanmar, known for its coastal location along the Andaman Sea and its largely rural, agriculture- and fishing-based communities.

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_69f76efa37088190be5416b7ef1ca275 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc91df97c8190ab8d16bfd5351228 completed May 6, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a415433c9d4819098696f85a1125c87 completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a4154ac9b788190b6c6100d26bbfb4d completed June 28, 2026, 5:06 p.m.
NED2 Entity disambiguation (via description) batch_6a41552062048190916933791c8925e2 completed June 28, 2026, 5:08 p.m.
Created at: May 3, 2026, 4:20 p.m.