Triple

T16627441
Position Surface form Disambiguated ID Type / Status
Subject Kita-ku, Osaka E403985 entity
Predicate contains P35 FINISHED
Object Tenma
Tenma is a historic district in Osaka, Japan, known for its bustling Tenjinbashi-suji shopping street, traditional eateries, and lively local atmosphere.
 E1224775 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: Tenma | Statement: [Kita-ku, Osaka, contains, Tenma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tenma
Context triple: [Kita-ku, Osaka, contains, Tenma]
  • A. Ikegami
    Ikegami is a neighborhood in Tokyo known for its historic Ikegami Honmon-ji temple and traditional atmosphere within the Ōta ward.
  • B. Yoshimura
    Yoshimura is a Japanese surname borne by various notable individuals across fields such as politics, sports, and the arts.
  • C. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • D. Yuasa
    Yuasa is a historic coastal town in Japan renowned as the birthplace of traditional soy sauce production.
  • E. Aoto
    Aoto is a neighborhood in Tokyo, Japan, located within Katsushika Ward and known as a residential and commercial area with convenient rail access.
  • 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: Tenma
Triple: [Kita-ku, Osaka, contains, Tenma]
Generated description
Tenma is a historic district in Osaka, Japan, known for its bustling Tenjinbashi-suji shopping street, traditional eateries, and lively local atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tenma
Target entity description: Tenma is a historic district in Osaka, Japan, known for its bustling Tenjinbashi-suji shopping street, traditional eateries, and lively local atmosphere.
  • A. Ikegami
    Ikegami is a neighborhood in Tokyo known for its historic Ikegami Honmon-ji temple and traditional atmosphere within the Ōta ward.
  • B. Yoshimura
    Yoshimura is a Japanese surname borne by various notable individuals across fields such as politics, sports, and the arts.
  • C. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • D. Yuasa
    Yuasa is a historic coastal town in Japan renowned as the birthplace of traditional soy sauce production.
  • E. Aoto
    Aoto is a neighborhood in Tokyo, Japan, located within Katsushika Ward and known as a residential and commercial area with convenient rail access.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e2683481908c9a5ed895a09a6e completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dba91bc819090a78ac4c0c01fc8 completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a007e747eac81908b0b5a2072a177dd completed May 10, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_6a007f75e7e48190ac5cf912cca60d9c completed May 10, 2026, 12:52 p.m.
Created at: April 10, 2026, 5:17 a.m.