Triple

T29456232
Position Surface form Disambiguated ID Type / Status
Subject Franco-Turkish War E747107 entity
Predicate belligerent P375 FINISHED
Object Armenian Legion
The Armenian Legion was a military unit composed mainly of Armenian volunteers that fought alongside French forces during and after World War I, particularly in campaigns against the Ottoman Empire.
E1869219 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: Armenian Legion | Statement: [Franco-Turkish War, belligerent, Armenian Legion]
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: Armenian Legion
Triple: [Franco-Turkish War, belligerent, Armenian Legion]
Generated description
The Armenian Legion was a military unit composed mainly of Armenian volunteers that fought alongside French forces during and after World War I, particularly in campaigns against the Ottoman Empire.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66b6cf8fc81909cd68959b362dde0 completed May 2, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f10d15b48190971ee421c5867aaf completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f5aca5e08190979b3eda92550523 completed June 7, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_6a25f981161481908aeb778528321059 completed June 7, 2026, 11:06 p.m.
Created at: April 28, 2026, 3:37 p.m.