Triple

T31687005
Position Surface form Disambiguated ID Type / Status
Subject Run (2020 film) E808687 entity
Predicate starring P1507 FINISHED
Object Kiera Allen
Kiera Allen is an American actress best known for her breakout leading role in the thriller film "Run" (2020), where she gained recognition as one of the first wheelchair-using actors to star in a major Hollywood thriller.
E1975827 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: Kiera Allen | Statement: [Run (2020 film), starring, Kiera Allen]
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: Kiera Allen
Triple: [Run (2020 film), starring, Kiera Allen]
Generated description
Kiera Allen is an American actress best known for her breakout leading role in the thriller film "Run" (2020), where she gained recognition as one of the first wheelchair-using actors to star in a major Hollywood thriller.

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_69f348ddcbc48190950cabcc25ff29b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa7d9248819093ccd69440d0cbe4 completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b9469741c8190b479b974c92fe18e completed June 12, 2026, 5:08 a.m.
NEDg Description generation batch_6a2b955c66288190bdca1c3033f59c7c completed June 12, 2026, 5:13 a.m.
NED2 Entity disambiguation (via description) batch_6a2b967c9eb48190bb9b86d606233de2 completed June 12, 2026, 5:17 a.m.
Created at: April 30, 2026, 11:07 p.m.