Triple

T32247564
Position Surface form Disambiguated ID Type / Status
Subject The Nut Job 2: Nutty by Nature E823792 entity
Predicate mainSetting P1957 FINISHED
Object Liberty Park
Liberty Park is the central urban green space where the animated animal characters live and stage their adventures in the film "The Nut Job 2: Nutty by Nature."
E2286583 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: Liberty Park | Statement: [The Nut Job 2: Nutty by Nature, mainSetting, Liberty Park]
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: Liberty Park
Triple: [The Nut Job 2: Nutty by Nature, mainSetting, Liberty Park]
Generated description
Liberty Park is the central urban green space where the animated animal characters live and stage their adventures in the film "The Nut Job 2: Nutty by Nature."

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_69f3490cdda88190a9d61e11252a771f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bc34616481908aee15d62ced6d46 completed May 3, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a46c5baa9888190ba0606d2166cd548 completed July 2, 2026, 8:10 p.m.
NEDg Description generation batch_6a46c68e538c8190890c3c9b7f88063e completed July 2, 2026, 8:14 p.m.
NED2 Entity disambiguation (via description) batch_6a46c6e69a9c81909cd503b06dc73eb1 completed July 2, 2026, 8:15 p.m.
Created at: May 1, 2026, 12:40 a.m.