Triple

T34110176
Position Surface form Disambiguated ID Type / Status
Subject Nanmyin Watchtower E874816 entity
Predicate partOf P40 FINISHED
Object royal palace complex of Ava
The royal palace complex of Ava was the fortified royal residence and administrative center of the Ava Kingdom, a major Burmese capital from the 14th to 16th centuries.
E2083070 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: royal palace complex of Ava | Statement: [Nanmyin Watchtower, partOf, royal palace complex of Ava]
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: royal palace complex of Ava
Triple: [Nanmyin Watchtower, partOf, royal palace complex of Ava]
Generated description
The royal palace complex of Ava was the fortified royal residence and administrative center of the Ava Kingdom, a major Burmese capital from the 14th to 16th centuries.

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_69f349a80d4481908527317d43f5c579 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70cb47b9c8190a479877960b256a6 completed May 3, 2026, 8:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36b7692b188190aadcf52ff42324d3 completed June 20, 2026, 3:53 p.m.
NEDg Description generation batch_6a36b81e1e588190bb400c76f45944d1 completed June 20, 2026, 3:56 p.m.
NED2 Entity disambiguation (via description) batch_6a36b989a6d081908c6873c7dc63cc99 completed June 20, 2026, 4:02 p.m.
Created at: May 1, 2026, 1:53 a.m.