Triple

T35660346
Position Surface form Disambiguated ID Type / Status
Subject Ilfenesh Hadera E1030414 entity
Predicate portrayedCharacter P1668 FINISHED
Object Stephanie Holden in Baywatch (2017 film)
Stephanie Holden in the 2017 Baywatch film is a capable and confident member of the lifeguard team who serves as a key ally and professional counterpart to Mitch Buchannon.
E2148965 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: Stephanie Holden in Baywatch (2017 film) | Statement: [Ilfenesh Hadera, portrayedCharacter, Stephanie Holden in Baywatch (2017 film)]
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: Stephanie Holden in Baywatch (2017 film)
Triple: [Ilfenesh Hadera, portrayedCharacter, Stephanie Holden in Baywatch (2017 film)]
Generated description
Stephanie Holden in the 2017 Baywatch film is a capable and confident member of the lifeguard team who serves as a key ally and professional counterpart to Mitch Buchannon.

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_69f76e09f87881909c954aaac176c34f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f7aa7b88190a52ff8ef9ceddf54 completed May 3, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38686341d881909fb00c32cc343c21 completed June 21, 2026, 10:40 p.m.
NEDg Description generation batch_6a3869287d9c81908a9083ca8ac5552c completed June 21, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a386984d2d08190a6b43ae7e6f7d5bb completed June 21, 2026, 10:45 p.m.
Created at: May 3, 2026, 4:05 p.m.