Triple

T29138815
Position Surface form Disambiguated ID Type / Status
Subject Jacob Keyes E738573 entity
Predicate education P5 FINISHED
Object UNSC Naval Academy
The UNSC Naval Academy is a prestigious military training institution in the Halo universe that educates and commissions officers for service in the United Nations Space Command Navy.
E1850659 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: UNSC Naval Academy | Statement: [Jacob Keyes, education, UNSC Naval Academy]
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: UNSC Naval Academy
Triple: [Jacob Keyes, education, UNSC Naval Academy]
Generated description
The UNSC Naval Academy is a prestigious military training institution in the Halo universe that educates and commissions officers for service in the United Nations Space Command Navy.

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_69f07cb3adb48190a9e0e169cd026634 completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f6626dee588190ae10942e2a9bff64 completed May 2, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537da0ff08190aba9fbe8a80f020e completed June 7, 2026, 9:20 a.m.
NEDg Description generation batch_6a253c4ed4fc81908e479403c939f813 completed June 7, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_6a25405315548190b3f08aace49bc72f completed June 7, 2026, 9:56 a.m.
Created at: April 28, 2026, 11:35 a.m.