Triple

T28670907
Position Surface form Disambiguated ID Type / Status
Subject Robert Graf E725714 entity
Predicate notableWork P4 FINISHED
Object Battle of the Sexes
Battle of the Sexes is a 2017 biographical sports comedy-drama film that portrays the famous 1973 tennis match between Billie Jean King and Bobby Riggs, exploring themes of gender equality and personal identity.
E194742 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: Battle of the Sexes | Statement: [Robert Graf, notableWork, Battle of the Sexes]
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: Battle of the Sexes
Triple: [Robert Graf, notableWork, Battle of the Sexes]
Generated description
Battle of the Sexes is a 2017 biographical sports comedy-drama film that portrays the famous 1973 tennis match between Billie Jean King and Bobby Riggs, exploring themes of gender equality and personal identity.

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_69f01d85be388190b669a0e401e2f2c4 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f656309dac8190b9b15e9fdb662950 completed May 2, 2026, 7:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec2070388190a64b7c042fff35e5 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f0319b708190b5d3a875fbc6810c completed June 7, 2026, 4:14 a.m.
NED2 Entity disambiguation (via description) batch_6a24f43f7cb881909d591ee6248b6c2b completed June 7, 2026, 4:31 a.m.
Created at: April 28, 2026, 5:03 a.m.