Triple

T31610741
Position Surface form Disambiguated ID Type / Status
Subject Hello I Must Be Going E806617 entity
Predicate mainCharacter P1183 FINISHED
Object Amy Minsky
Amy Minsky is the recently divorced, emotionally adrift woman in the film "Hello I Must Be Going" who begins an unexpected relationship that helps her rediscover a sense of purpose and self-worth.
 E2066868 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: Amy Minsky | Statement: [Hello I Must Be Going, mainCharacter, Amy Minsky]
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: Amy Minsky
Triple: [Hello I Must Be Going, mainCharacter, Amy Minsky]
Generated description
Amy Minsky is the recently divorced, emotionally adrift woman in the film "Hello I Must Be Going" who begins an unexpected relationship that helps her rediscover a sense of purpose and self-worth.

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_69f348d61f2081908cad94bc9ffbb671 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a873357481909a3499827e927cda completed May 3, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36655640e88190a9a631558cf2651a completed June 20, 2026, 10:03 a.m.
NEDg Description generation batch_6a366626e0708190b7b11d854a951965 completed June 20, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a3666c1d1b881908654acaa4b5898ec completed June 20, 2026, 10:09 a.m.
Created at: April 30, 2026, 10:36 p.m.