Triple

T9010214
Position Surface form Disambiguated ID Type / Status
Subject Hang Gai Street E215447 entity
Predicate hasNearbyAttraction P2064 FINISHED
Object Hang Bong Street
Hang Bong Street is a bustling historic street in Hanoi’s Old Quarter, known for its traditional shops, tailors, and textile stores.
 E772647 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: Hang Bong Street | Statement: [Hang Gai Street, hasNearbyAttraction, Hang Bong Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hang Bong Street
Context triple: [Hang Gai Street, hasNearbyAttraction, Hang Bong Street]
  • A. Munsu Street
    Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
  • B. Gangdong-dong
    Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
  • C. Singil-dong
    Singil-dong is a neighborhood (dong) in Seoul, South Korea, located within the city's southwestern Yeongdeungpo District.
  • D. Kim Mã Street
    Kim Mã Street is a major, historically significant thoroughfare in central Hanoi, Vietnam, known for its busy traffic, commercial activity, and connection to key administrative and cultural areas.
  • E. Cheonghak-dong
    Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
  • 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: Hang Bong Street
Triple: [Hang Gai Street, hasNearbyAttraction, Hang Bong Street]
Generated description
Hang Bong Street is a bustling historic street in Hanoi’s Old Quarter, known for its traditional shops, tailors, and textile stores.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hang Bong Street
Target entity description: Hang Bong Street is a bustling historic street in Hanoi’s Old Quarter, known for its traditional shops, tailors, and textile stores.
  • A. Munsu Street
    Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
  • B. Gangdong-dong
    Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
  • C. Singil-dong
    Singil-dong is a neighborhood (dong) in Seoul, South Korea, located within the city's southwestern Yeongdeungpo District.
  • D. Kim Mã Street
    Kim Mã Street is a major, historically significant thoroughfare in central Hanoi, Vietnam, known for its busy traffic, commercial activity, and connection to key administrative and cultural areas.
  • E. Cheonghak-dong
    Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69c00ae8819090786385a72e8baf completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9dca848190952427bb5712081f completed April 3, 2026, 3:24 p.m.
NEDg Description generation batch_69cfdc5b230881908057cc868e44ea44 completed April 3, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69cfdcfc28288190b849b3f0216a7e9a completed April 3, 2026, 3:30 p.m.
Created at: March 30, 2026, 7:06 p.m.