Triple

T7877869
Position Surface form Disambiguated ID Type / Status
Subject Cao Wei E182901 entity
Predicate usedCalendarEraName P36399 FINISHED
Object Taihe
Taihe was a historical Chinese era name used during the Three Kingdoms period under the state of Cao Wei.
 E701616 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: Taihe | Statement: [Cao Wei, usedCalendarEraName, Taihe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taihe
Context triple: [Cao Wei, usedCalendarEraName, Taihe]
  • A. Izumi
    Izumi is a city located in Osaka Prefecture, Japan, known as a residential and commercial hub in the Kansai region.
  • B. Kamogawa
    Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
  • C. Kamogawa
    Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
  • D. Guri
    Guri is a city in South Korea located just east of Seoul, known as a suburban residential area with historical sites and access to natural scenery.
  • E. Ogawa
    Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
  • 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: Taihe
Triple: [Cao Wei, usedCalendarEraName, Taihe]
Generated description
Taihe was a historical Chinese era name used during the Three Kingdoms period under the state of Cao Wei.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taihe
Target entity description: Taihe was a historical Chinese era name used during the Three Kingdoms period under the state of Cao Wei.
  • A. Izumi
    Izumi is a city located in Osaka Prefecture, Japan, known as a residential and commercial hub in the Kansai region.
  • B. Kamogawa
    Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
  • C. Kamogawa
    Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
  • D. Guri
    Guri is a city in South Korea located just east of Seoul, known as a suburban residential area with historical sites and access to natural scenery.
  • E. Ogawa
    Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
  • 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_69ca828a17248190b46defe758bc5ad3 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39bd64e481909f699e7dd2818b8f completed March 31, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b7fef308190bbc74e13f4205192 completed March 31, 2026, 5:28 a.m.
NEDg Description generation batch_69cb7630b8908190a0b8f4856bceea0a completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbbfb894588190971ade076acdbd5c completed March 31, 2026, 12:36 p.m.
Created at: March 30, 2026, 4:57 p.m.