Triple

T27273185
Position Surface form Disambiguated ID Type / Status
Subject Donald Nordley E688111 entity
Predicate appearsAlongsideCharacter P25756 FINISHED
Object Eloise "Honey Bear" Kelly
Eloise "Honey Bear" Kelly is a fictional character, likely from a film or television work, known for appearing in scenes alongside the character Donald Nordley.
E1764910 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: Eloise "Honey Bear" Kelly | Statement: [Donald Nordley, appearsAlongsideCharacter, Eloise "Honey Bear" Kelly]
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: Eloise "Honey Bear" Kelly
Triple: [Donald Nordley, appearsAlongsideCharacter, Eloise "Honey Bear" Kelly]
Generated description
Eloise "Honey Bear" Kelly is a fictional character, likely from a film or television work, known for appearing in scenes alongside the character Donald Nordley.

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_69ef3558cf8881909595ef89daf6e14a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62725b5d48190b5defc0995e6a481 completed May 2, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12628f499c81908d6cd6f2fc00a5c1 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a12691f148c81908af5cdfb6bbe9948 completed May 24, 2026, 2:57 a.m.
NED2 Entity disambiguation (via description) batch_6a126983a194819093db115c63acc22f completed May 24, 2026, 2:59 a.m.
Created at: April 27, 2026, 11 a.m.