Triple

T25012794
Position Surface form Disambiguated ID Type / Status
Subject High Road to China E626039 entity
Predicate leadActorRole P5563 FINISHED
Object Bess Armstrong as Eve Tozer
Bess Armstrong as Eve Tozer is the spirited, headstrong heiress who hires a jaded pilot to help her search for her missing father in the 1983 adventure film "High Road to China."
E1659315 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: Bess Armstrong as Eve Tozer | Statement: [High Road to China, leadActorRole, Bess Armstrong as Eve Tozer]
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: Bess Armstrong as Eve Tozer
Triple: [High Road to China, leadActorRole, Bess Armstrong as Eve Tozer]
Generated description
Bess Armstrong as Eve Tozer is the spirited, headstrong heiress who hires a jaded pilot to help her search for her missing father in the 1983 adventure film "High Road to China."

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44ba244b8819089eca266db61d314 completed May 1, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10337768088190922cb43e9e1d7934 completed May 22, 2026, 10:44 a.m.
NEDg Description generation batch_6a103440c3bc8190aed8b908ec08143e completed May 22, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a103516e0e88190898a8b019ff7e6e5 completed May 22, 2026, 10:51 a.m.
Created at: April 18, 2026, 6:05 a.m.