Triple

T14939265
Position Surface form Disambiguated ID Type / Status
Subject The Prince of Broadway (Japanese production) E372477 entity
Predicate hasCastMember P2308 FINISHED
Object Shinji Takeda
Shinji Takeda is a Japanese actor and musician known for his roles in television dramas, films, and stage productions.
E1890424 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: Shinji Takeda | Statement: [The Prince of Broadway (Japanese production), hasCastMember, Shinji Takeda]
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: Shinji Takeda
Triple: [The Prince of Broadway (Japanese production), hasCastMember, Shinji Takeda]
Generated description
Shinji Takeda is a Japanese actor and musician known for his roles in television dramas, films, and stage productions.

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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64a2f24819099b21566756668a2 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a26f19ad7c48190b01dfaea5f71b7bd completed June 8, 2026, 4:45 p.m.
NEDg Description generation batch_6a26f66b547081909ac88e14bf340493 completed June 8, 2026, 5:05 p.m.
NED2 Entity disambiguation (via description) batch_6a26f7d1e25481909fbe21144c0c22b6 completed June 8, 2026, 5:11 p.m.
Created at: April 10, 2026, 2:38 a.m.