Triple

T38367450
Position Surface form Disambiguated ID Type / Status
Subject Shanghai urban road network E892486 entity
Predicate integratedWith P2830 FINISHED
Object Shanghai port facilities
Shanghai port facilities comprise one of the world’s busiest and most advanced maritime hubs, featuring extensive container terminals, logistics centers, and supporting infrastructure that drive the city’s global trade and shipping activities.
E48168 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: Shanghai port facilities | Statement: [Shanghai urban road network, integratedWith, Shanghai port facilities]
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: Shanghai port facilities
Triple: [Shanghai urban road network, integratedWith, Shanghai port facilities]
Generated description
Shanghai port facilities comprise one of the world’s busiest and most advanced maritime hubs, featuring extensive container terminals, logistics centers, and supporting infrastructure that drive the city’s global trade and shipping activities.

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_69f76e47cb4c8190bdd92cd1db59c0c5 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fcc776a4e081909b1b4e46725e357a completed May 7, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b29d28608190aa7a111f3cedeb09 completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b3fbfcc88190ae07b7f0b578aa30 completed June 28, 2026, 11:53 p.m.
NED2 Entity disambiguation (via description) batch_6a41b4ab67288190bf774036d4fe05e2 completed June 28, 2026, 11:56 p.m.
Created at: May 3, 2026, 4:31 p.m.