Triple

T26455388
Position Surface form Disambiguated ID Type / Status
Subject Beigan Township E665469 entity
Predicate hasIsland P970 FINISHED
Object Liji Island
Liji Island is a small outlying island of Taiwan located in the Matsu archipelago off the coast of mainland China.
E2296101 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: Liji Island | Statement: [Beigan Township, hasIsland, Liji Island]
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: Liji Island
Triple: [Beigan Township, hasIsland, Liji Island]
Generated description
Liji Island is a small outlying island of Taiwan located in the Matsu archipelago off the coast of mainland China.

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_69ee883d5040819097dd154643005230 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f61268e08c8190a29c2ae279d098d9 completed May 2, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82350775b48190b84c1d74a9264d78 completed Aug. 16, 2026, 10:09 p.m.
NEDg Description generation batch_6a823573fbac8190ba977bc3d182d8ec completed Aug. 16, 2026, 10:11 p.m.
NED2 Entity disambiguation (via description) batch_6a8235b4ccf48190bc0aed4a747999fe completed Aug. 16, 2026, 10:12 p.m.
Created at: April 27, 2026, 12:08 a.m.