Triple

T15399853
Position Surface form Disambiguated ID Type / Status
Subject Northern Kantō urban area E368282 entity
Predicate hasMajorCity P316 FINISHED
Object Ota
Ōta is a major industrial city in Japan’s northern Kantō region, known especially for its automotive manufacturing, including the headquarters and main plants of Subaru.
 E1154944 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: Ota | Statement: [Northern Kantō urban area, hasMajorCity, Ota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ota
Context triple: [Northern Kantō urban area, hasMajorCity, Ota]
  • A. Ota
    Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
  • B. Ota
    Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
  • C. Olta
    Olta is a small town in the La Rioja Province of northwestern Argentina that serves as an administrative and service center for the surrounding rural region.
  • D. Ootha
    Ootha is a small rural locality in New South Wales, Australia, situated within the Forbes Shire local government area.
  • E. Oza
    "Oza" is a prominent poetic work by Russian poet Andrei Voznesensky, reflecting his innovative style and experimental approach to verse.
  • 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: Ota
Triple: [Northern Kantō urban area, hasMajorCity, Ota]
Generated description
Ōta is a major industrial city in Japan’s northern Kantō region, known especially for its automotive manufacturing, including the headquarters and main plants of Subaru.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ota
Target entity description: Ōta is a major industrial city in Japan’s northern Kantō region, known especially for its automotive manufacturing, including the headquarters and main plants of Subaru.
  • A. Ota
    Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
  • B. Ota
    Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
  • C. Olta
    Olta is a small town in the La Rioja Province of northwestern Argentina that serves as an administrative and service center for the surrounding rural region.
  • D. Ootha
    Ootha is a small rural locality in New South Wales, Australia, situated within the Forbes Shire local government area.
  • E. Oza
    "Oza" is a prominent poetic work by Russian poet Andrei Voznesensky, reflecting his innovative style and experimental approach to verse.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8d89e08190b7cae778d89fb5e1 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13567e3481908eb6293c6af35f3a completed May 9, 2026, 10:58 a.m.
NEDg Description generation batch_69ff144af00481909191a2d33874c195 completed May 9, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69ff15ae7c9c81909fd0894e48e5b5b1 completed May 9, 2026, 11:08 a.m.
Created at: April 10, 2026, 3:19 a.m.