Triple

T31234156
Position Surface form Disambiguated ID Type / Status
Subject Intersection E796368 entity
Predicate characterPortrayedBy P1507 FINISHED
Object Vincent Eastman – Richard Gere
Vincent Eastman is the conflicted architect protagonist in the romantic drama film "Intersection," portrayed by actor Richard Gere.
 E1954292 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: Vincent Eastman – Richard Gere | Statement: [Intersection, characterPortrayedBy, Vincent Eastman – Richard Gere]
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: Vincent Eastman – Richard Gere
Triple: [Intersection, characterPortrayedBy, Vincent Eastman – Richard Gere]
Generated description
Vincent Eastman is the conflicted architect protagonist in the romantic drama film "Intersection," portrayed by actor Richard Gere.

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_69f224db69ac81909a370adad6a7ac7c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d212650819088514cd8d7f141d9 completed May 3, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296be37e808190b40093c547ac0948 completed June 10, 2026, 1:51 p.m.
NEDg Description generation batch_6a296e620d848190a2c4cd9fd856a51e completed June 10, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_6a29b08214cc8190afc22720b20e6afb completed June 10, 2026, 6:44 p.m.
Created at: April 29, 2026, 9:10 p.m.