Triple

T34986090
Position Surface form Disambiguated ID Type / Status
Subject Excelsior class E1008949 entity
Predicate successorOf P78 FINISHED
Object Constitution class
The Constitution class is a famed Federation starship class in the Star Trek universe, best known for vessels like the USS Enterprise that played central roles in 23rd-century exploration and conflicts.
E2120524 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: Constitution class | Statement: [Excelsior class, successorOf, Constitution class]
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: Constitution class
Triple: [Excelsior class, successorOf, Constitution class]
Generated description
The Constitution class is a famed Federation starship class in the Star Trek universe, best known for vessels like the USS Enterprise that played central roles in 23rd-century exploration and 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_69f76dc844a48190881951fffb83d17e completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7849d996481909baf92a2d8b69133 completed May 3, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b28457b081909ac991525cf48d68 completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b35f30b48190a2ef8bf97859463a completed June 21, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_6a37b473ee748190b8f75b46a188bf5f completed June 21, 2026, 9:52 a.m.
Created at: May 3, 2026, 4:01 p.m.