Triple

T31307073
Position Surface form Disambiguated ID Type / Status
Subject The Inkwell E798360 entity
Predicate mainCharacter P1183 FINISHED
Object Drew Tate
Drew Tate is the protagonist of the film "The Inkwell," a troubled yet introspective teenager navigating family tensions and personal growth during a summer vacation on Martha’s Vineyard in the 1970s.
E1963210 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: Drew Tate | Statement: [The Inkwell, mainCharacter, Drew Tate]
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: Drew Tate
Triple: [The Inkwell, mainCharacter, Drew Tate]
Generated description
Drew Tate is the protagonist of the film "The Inkwell," a troubled yet introspective teenager navigating family tensions and personal growth during a summer vacation on Martha’s Vineyard in the 1970s.

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_69f224e0bd4c8190aab9b29a73f7aa3c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69e64810c8190858188395ca5f979 completed May 3, 2026, 1:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b075df4a481909286f36d0448b8a3 completed June 11, 2026, 7:07 p.m.
NEDg Description generation batch_6a2b0a68765881908c9f514be8ae4054 completed June 11, 2026, 7:20 p.m.
NED2 Entity disambiguation (via description) batch_6a2b0aca83208190a9718df79f2d2e5a completed June 11, 2026, 7:21 p.m.
Created at: April 29, 2026, 9:14 p.m.