Triple

T36623673
Position Surface form Disambiguated ID Type / Status
Subject Instant Family E904111 entity
Predicate mainCharacter P1183 FINISHED
Object Pete Wagner
Pete Wagner is the well-meaning but initially overwhelmed father figure in the comedy-drama film "Instant Family," who, along with his wife, adopts three siblings and learns to navigate the challenges of foster parenting.
E2193162 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: Pete Wagner | Statement: [Instant Family, mainCharacter, Pete Wagner]
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: Pete Wagner
Triple: [Instant Family, mainCharacter, Pete Wagner]
Generated description
Pete Wagner is the well-meaning but initially overwhelmed father figure in the comedy-drama film "Instant Family," who, along with his wife, adopts three siblings and learns to navigate the challenges of foster parenting.

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_69f76e6ae750819096911e6e2d4d12c5 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c4ae720c81908c2643c95a726807 completed May 3, 2026, 9:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a09644d5c819088de7ad42a764fe4 completed June 23, 2026, 4:19 a.m.
NEDg Description generation batch_6a3a0cec02d48190b4770d012b5208a4 completed June 23, 2026, 4:34 a.m.
NED2 Entity disambiguation (via description) batch_6a3a179310d08190a89d4feaf3e4c6e0 completed June 23, 2026, 5:20 a.m.
Created at: May 3, 2026, 4:11 p.m.