Triple

T36894018
Position Surface form Disambiguated ID Type / Status
Subject shrine to Jobu E911837 entity
Predicate filmFranchise P5564 FINISHED
Object Major League series
The Major League series is a comedic baseball film franchise that follows the misfit Cleveland Indians team as they overcome inept ownership, internal conflicts, and long odds to find success on the field.
E2202905 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: Major League series | Statement: [shrine to Jobu, filmFranchise, Major League series]
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: Major League series
Triple: [shrine to Jobu, filmFranchise, Major League series]
Generated description
The Major League series is a comedic baseball film franchise that follows the misfit Cleveland Indians team as they overcome inept ownership, internal conflicts, and long odds to find success on the field.

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_69f76e841b54819097e7fa768bbc70b2 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd8c70388190b6e63d110dfcf7ed completed May 5, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfaf896608190838ad0450ade66d7 completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3dfd893adc819090d54e0cf1e01138 completed June 26, 2026, 4:18 a.m.
NED2 Entity disambiguation (via description) batch_6a3e064adfcc8190af3578eb4e77eb74 completed June 26, 2026, 4:55 a.m.
Created at: May 3, 2026, 4:13 p.m.