Triple

T24430557
Position Surface form Disambiguated ID Type / Status
Subject Casey Jones E615991 entity
Predicate fullName P16 FINISHED
Object Arnold Casey Jones
Arnold Casey Jones, better known as Casey Jones, is a fictional vigilante ally of the Teenage Mutant Ninja Turtles, recognized for his hockey mask and sports-equipment-based crime-fighting.
 E1641144 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: Arnold Casey Jones | Statement: [Casey Jones, fullName, Arnold Casey Jones]
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: Arnold Casey Jones
Triple: [Casey Jones, fullName, Arnold Casey Jones]
Generated description
Arnold Casey Jones, better known as Casey Jones, is a fictional vigilante ally of the Teenage Mutant Ninja Turtles, recognized for his hockey mask and sports-equipment-based crime-fighting.

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_69e2d7eadb248190a867130fe45f0388 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29782a4a0819087cb7ba399371520 completed April 29, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0ff845d4d881909f22c10823af51ec completed May 22, 2026, 6:31 a.m.
NEDg Description generation batch_6a0ff956f6e48190950c5bace85c9669 completed May 22, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff9feda34819084e79982606c3972 completed May 22, 2026, 6:38 a.m.
Created at: April 18, 2026, 2:16 a.m.