Triple

T23824148
Position Surface form Disambiguated ID Type / Status
Subject The Best Man Holiday E589318 entity
Predicate featuresCharacter P626 FINISHED
Object Candace
Candace is a fictional character in the ensemble romantic comedy-drama film "The Best Man Holiday," known for her role in the intertwined personal and relational dramas of the main cast.
E1607417 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: Candace | Statement: [The Best Man Holiday, featuresCharacter, Candace]
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: Candace
Triple: [The Best Man Holiday, featuresCharacter, Candace]
Generated description
Candace is a fictional character in the ensemble romantic comedy-drama film "The Best Man Holiday," known for her role in the intertwined personal and relational dramas of the main cast.

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_69e25d1922d481909cab567c06a802ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7b12520819086daf8c284732e0f completed April 29, 2026, 8:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7611da8881908b63434f71e7e560 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f76cc78748190b0f22716094bba19 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77541b948190bb866a8c7c6f5ca9 completed May 21, 2026, 9:21 p.m.
Created at: April 17, 2026, 7:59 p.m.