Triple

T28718199
Position Surface form Disambiguated ID Type / Status
Subject Oats Studios E730018 entity
Predicate notableWork P4 FINISHED
Object God: Serengeti
"God: Serengeti" is a short experimental sci-fi film by Oats Studios that portrays a godlike being casually manipulating the creation and destruction of life on Earth’s Serengeti.
E1830256 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: God: Serengeti | Statement: [Oats Studios, notableWork, God: Serengeti]
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: God: Serengeti
Triple: [Oats Studios, notableWork, God: Serengeti]
Generated description
"God: Serengeti" is a short experimental sci-fi film by Oats Studios that portrays a godlike being casually manipulating the creation and destruction of life on Earth’s Serengeti.

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_69f043e91fe48190b73bcd8e08d433e0 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65706d96081909df278575e3c67f0 completed May 2, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf5a7070819093d09c890467a0b4 completed June 1, 2026, 12:16 a.m.
NEDg Description generation batch_6a1cd021944881908cae19ba344f1184 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a249457116881909199d0b381a902c3 completed June 6, 2026, 9:42 p.m.
Created at: April 28, 2026, 5:52 a.m.