Triple

T23259394
Position Surface form Disambiguated ID Type / Status
Subject Banpo Bridge E581961 entity
Predicate near P350 FINISHED
Object Hannam Bridge
Hannam Bridge is a major road bridge spanning the Han River in Seoul, South Korea, connecting the districts of Yongsan and Gangnam.
E1632263 NE FINISHED

How this triple was built (2 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: Hannam Bridge | Statement: [Banpo Bridge, near, Hannam Bridge]
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: Hannam Bridge
Triple: [Banpo Bridge, near, Hannam Bridge]
Generated description
Hannam Bridge is a major road bridge spanning the Han River in Seoul, South Korea, connecting the districts of Yongsan and Gangnam.

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_69e246079f58819085eaa9c260906880 completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f194c7ec148190b01fd215a0c1daa1 completed April 29, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd62284d8819087fc65fb7f29c3a4 completed May 22, 2026, 4:05 a.m.
NEDg Description generation batch_6a0fd85e69f88190a71fc997cda08329 completed May 22, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd8e5ce10819096e6cdff28c1b3a2 completed May 22, 2026, 4:17 a.m.
Created at: April 17, 2026, 4:11 p.m.