Triple

T14611135
Position Surface form Disambiguated ID Type / Status
Subject American Teen E342962 entity
Predicate producer P490 FINISHED
Object Hako
Hako is a music producer best known for working on the soundtrack of the coming-of-age film "American Teen."
 E1109760 NE FINISHED

How this triple was built (4 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: Hako | Statement: [American Teen, producer, Hako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hako
Context triple: [American Teen, producer, Hako]
  • A. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • B. Hakutaka
    Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
  • C. Bauko
    Bauko is a municipality in the Cordillera region of the northern Philippines known for its mountainous terrain, indigenous culture, and agricultural communities.
  • D. Hakha
    Hakha is a hill town in western Myanmar that serves as the administrative and cultural center of the Chin people.
  • E. Gohatto
    Gohatto is a 1999 Japanese period drama film directed by Nagisa Ōshima that explores forbidden desire and tensions within the samurai ranks of the Shinsengumi.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Hako
Triple: [American Teen, producer, Hako]
Generated description
Hako is a music producer best known for working on the soundtrack of the coming-of-age film "American Teen."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hako
Target entity description: Hako is a music producer best known for working on the soundtrack of the coming-of-age film "American Teen."
  • A. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • B. Hakutaka
    Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
  • C. Bauko
    Bauko is a municipality in the Cordillera region of the northern Philippines known for its mountainous terrain, indigenous culture, and agricultural communities.
  • D. Hakha
    Hakha is a hill town in western Myanmar that serves as the administrative and cultural center of the Chin people.
  • E. Gohatto
    Gohatto is a 1999 Japanese period drama film directed by Nagisa Ōshima that explores forbidden desire and tensions within the samurai ranks of the Shinsengumi.
  • F. None of above. chosen

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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb450e6588190a94488d8e71888c8 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda91f437c8190ada4d1c3708faedd completed May 8, 2026, 9:13 a.m.
NEDg Description generation batch_69fdb1ad32a4819088e5831f3d74ea4e completed May 8, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_69fdb316479c81909343196bb89e5e57 completed May 8, 2026, 9:55 a.m.
Created at: April 10, 2026, 1:25 a.m.