Triple

T29451765
Position Surface form Disambiguated ID Type / Status
Subject The Burmese Harp E746992 entity
Predicate editedBy P1954 FINISHED
Object Con Ichikawa
Con Ichikawa was a renowned Japanese film director and screenwriter known for his stylistic versatility and influential works spanning war dramas, literary adaptations, and social satires.
E1868006 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: Con Ichikawa | Statement: [The Burmese Harp, editedBy, Con Ichikawa]
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: Con Ichikawa
Triple: [The Burmese Harp, editedBy, Con Ichikawa]
Generated description
Con Ichikawa was a renowned Japanese film director and screenwriter known for his stylistic versatility and influential works spanning war dramas, literary adaptations, and social satires.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66b682f0c81908394f0f2f6ddc483 completed May 2, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d93faefc8190bec7c94794921f95 completed June 7, 2026, 8:49 p.m.
NEDg Description generation batch_6a25dd6da0f4819097a6c39da69d5e6e completed June 7, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_6a25e1a372c8819098b3fe3c7152633b completed June 7, 2026, 9:24 p.m.
Created at: April 28, 2026, 3:33 p.m.