Triple

T24542213
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Bay port cluster E607124 entity
Predicate hasPart P35 FINISHED
Object Port of Kimitsu
The Port of Kimitsu is a Japanese industrial seaport on Tokyo Bay, known primarily for serving large steelworks and heavy industry facilities.
E1686022 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: Port of Kimitsu | Statement: [Tokyo Bay port cluster, hasPart, Port of Kimitsu]
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: Port of Kimitsu
Triple: [Tokyo Bay port cluster, hasPart, Port of Kimitsu]
Generated description
The Port of Kimitsu is a Japanese industrial seaport on Tokyo Bay, known primarily for serving large steelworks and heavy industry facilities.

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_69e2c4c9bf94819082d05da6f5c29907 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8c5d320819083224ef63e7fffae completed April 30, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6ff45748190abf017541c32bcc9 completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b7fa6d60819097ff930865af4032 completed May 22, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_6a10b96e57f081908a75a191ce7bafce completed May 22, 2026, 8:15 p.m.
Created at: April 18, 2026, 2:26 a.m.