Triple

T28571748
Position Surface form Disambiguated ID Type / Status
Subject Eulmi Incident E723130 entity
Predicate alsoKnownAs P39 FINISHED
Object Eulmi Sabyeon
Eulmi Sabyeon is a historical Korean incident involving political turmoil and conflict during the late Joseon Dynasty.
E1825774 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: Eulmi Sabyeon | Statement: [Eulmi Incident, alsoKnownAs, Eulmi Sabyeon]
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: Eulmi Sabyeon
Triple: [Eulmi Incident, alsoKnownAs, Eulmi Sabyeon]
Generated description
Eulmi Sabyeon is a historical Korean incident involving political turmoil and conflict during the late Joseon Dynasty.

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_69f01d7e97708190ae9e77ee66a68abd completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f650930d088190982ac09775d5b177 completed May 2, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6ede350819082b45afbf848a7f3 completed May 31, 2026, 10:32 p.m.
NEDg Description generation batch_6a1cbadae2b88190923794f499874f0d completed May 31, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbb4e3c4081909221f3997a54efb7 completed May 31, 2026, 10:50 p.m.
Created at: April 28, 2026, 4:10 a.m.