Triple

T19116347
Position Surface form Disambiguated ID Type / Status
Subject Oh E467916 entity
Predicate hasNotableBearer P458 FINISHED
Object Oh Nami
Oh Nami is a South Korean actress known for her work in television dramas and films.
 E1360350 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: Oh Nami | Statement: [Oh, hasNotableBearer, Oh Nami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oh Nami
Context triple: [Oh, hasNotableBearer, Oh Nami]
  • A. Naniwa
    Naniwa is a historical name for the area that later became the city of Osaka in Japan, once an important ancient port and political center.
  • B. Nawat
    Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
  • C. Miyuki
    Miyuki is a Japanese given name commonly used for women and associated with meanings such as "beautiful happiness" or "deep snow," depending on the kanji used.
  • D. Nakoruru
    Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
  • E. Nakanokimi
    Nakanokimi is a noblewoman in Murasaki Shikibu’s classic Japanese novel "The Tale of Genji," known as one of Kaoru’s principal love interests.
  • 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: Oh Nami
Triple: [Oh, hasNotableBearer, Oh Nami]
Generated description
Oh Nami is a South Korean actress known for her work in television dramas and films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oh Nami
Target entity description: Oh Nami is a South Korean actress known for her work in television dramas and films.
  • A. Naniwa
    Naniwa is a historical name for the area that later became the city of Osaka in Japan, once an important ancient port and political center.
  • B. Nawat
    Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
  • C. Miyuki
    Miyuki is a Japanese given name commonly used for women and associated with meanings such as "beautiful happiness" or "deep snow," depending on the kanji used.
  • D. Nakoruru
    Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
  • E. Nakanokimi
    Nakanokimi is a noblewoman in Murasaki Shikibu’s classic Japanese novel "The Tale of Genji," known as one of Kaoru’s principal love interests.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3984bf48190818fa2b01b75decb completed April 20, 2026, 8:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05e66ffaf481909c31c007cb165147 completed May 14, 2026, 3:12 p.m.
NEDg Description generation batch_6a05e9cc2f90819082679876c6a713b5 completed May 14, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_6a06ee0aa8748190bf2ac6740f47c591 completed May 15, 2026, 9:57 a.m.
Created at: April 10, 2026, 12:05 p.m.