Triple

T24035745
Position Surface form Disambiguated ID Type / Status
Subject Moken language E595226 entity
Predicate alternateName P39 FINISHED
Object Morgan language
Morgan language is an Austroasiatic language spoken by the Moken (sea nomad) communities of the Mergui Archipelago and nearby coastal regions of Myanmar and Thailand.
E1615198 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: Morgan language | Statement: [Moken language, alternateName, Morgan language]
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: Morgan language
Triple: [Moken language, alternateName, Morgan language]
Generated description
Morgan language is an Austroasiatic language spoken by the Moken (sea nomad) communities of the Mergui Archipelago and nearby coastal regions of Myanmar and Thailand.

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_69e288bf45f08190a1b6ed8cd0b9e86b completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d8d43884819093e9207a99ae2a70 completed April 29, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7eaff24081908c0350d67a7d53dd completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f8279ac948190a740f3d0f8f64368 completed May 21, 2026, 10:08 p.m.
NED2 Entity disambiguation (via description) batch_6a0f8353faac8190b62a1d0523919f47 completed May 21, 2026, 10:12 p.m.
Created at: April 17, 2026, 9:56 p.m.