Triple

T18152713
Position Surface form Disambiguated ID Type / Status
Subject Battle of Asakai E434547 entity
Predicate tookPlaceInSystem P80276 FINISHED
Object Asakai
Asakai is a star system in the online game EVE Online, best known as the site of a massive, player-driven battle that became one of the game's most famous large-scale conflicts.
E1683536 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: Asakai | Statement: [Battle of Asakai, tookPlaceInSystem, Asakai]
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: Asakai
Triple: [Battle of Asakai, tookPlaceInSystem, Asakai]
Generated description
Asakai is a star system in the online game EVE Online, best known as the site of a massive, player-driven battle that became one of the game's most famous large-scale conflicts.

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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de39a8f481908d1752767d0aae0e completed April 19, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad18b43c8190bd2eb11a39566ed1 completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10adf21b3c8190a7388b1a74faf65e completed May 22, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a10af5c912c81908164148277047f40 completed May 22, 2026, 7:32 p.m.
Created at: April 10, 2026, 10:29 a.m.