Triple

T30475173
Position Surface form Disambiguated ID Type / Status
Subject Cái Mép–Thị Vải port complex E775422 entity
Predicate hasComponent P35 FINISHED
Object Cái Mép container terminals
Cái Mép container terminals are a major deep-water container handling hub in southern Vietnam, serving as a key gateway for international maritime trade.
E1916643 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: Cái Mép container terminals | Statement: [Cái Mép–Thị Vải port complex, hasComponent, Cái Mép container terminals]
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: Cái Mép container terminals
Triple: [Cái Mép–Thị Vải port complex, hasComponent, Cái Mép container terminals]
Generated description
Cái Mép container terminals are a major deep-water container handling hub in southern Vietnam, serving as a key gateway for international maritime trade.

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_69f22497341481909c21ba329fadaa6b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68718543c8190a173db3534b3c8ea completed May 2, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27ac22e5288190a21dd047aa1e049d completed June 9, 2026, 6:01 a.m.
NEDg Description generation batch_6a27ad3048ec81909f58b8f52a449e5c completed June 9, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a27adc727788190bf60ed1c2b80ce0c completed June 9, 2026, 6:08 a.m.
Created at: April 29, 2026, 8:11 p.m.