Triple

T26875086
Position Surface form Disambiguated ID Type / Status
Subject Mr. Potter (It's a Wonderful Life) E676725 entity
Predicate givenName P17 FINISHED
Object Henry
Henry is the first name of Mr. Potter, the wealthy, miserly antagonist in the classic film "It's a Wonderful Life."
E1311340 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: Henry | Statement: [Mr. Potter (It's a Wonderful Life), givenName, Henry]
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: Henry
Triple: [Mr. Potter (It's a Wonderful Life), givenName, Henry]
Generated description
Henry is the first name of Mr. Potter, the wealthy, miserly antagonist in the classic film "It's a Wonderful Life."

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_69eee9bb44988190b6e11652d028bc59 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f1721b081908875cb210bee4d08 completed May 2, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229847bac81908db3370e106f1fcb completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122b1547d48190993350cd89974e90 completed May 23, 2026, 10:32 p.m.
NED2 Entity disambiguation (via description) batch_6a122c19dd14819093692713467547d5 completed May 23, 2026, 10:37 p.m.
Created at: April 27, 2026, 5:35 a.m.