Triple

T24420259
Position Surface form Disambiguated ID Type / Status
Subject Mexican Pacific ports system E615704 entity
Predicate hasComponent P35 FINISHED
Object Port of Puerto Chiapas
The Port of Puerto Chiapas is a commercial and cruise seaport in southern Mexico near the Guatemalan border, serving as a regional hub for trade and tourism on the Pacific coast.
E1675804 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 Puerto Chiapas | Statement: [Mexican Pacific ports system, hasComponent, Port of Puerto Chiapas]
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 Puerto Chiapas
Triple: [Mexican Pacific ports system, hasComponent, Port of Puerto Chiapas]
Generated description
The Port of Puerto Chiapas is a commercial and cruise seaport in southern Mexico near the Guatemalan border, serving as a regional hub for trade and tourism on the Pacific coast.

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_69e2d7e9bfac8190a748952a90957106 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f296a227d08190bd4e3e4832c5a205 completed April 29, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1075a3ad608190b15cd43f46bd6cd0 completed May 22, 2026, 3:26 p.m.
NEDg Description generation batch_6a1076b9b58881908eb0b619471c3879 completed May 22, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1077d01fa08190b5439eba879538ef completed May 22, 2026, 3:35 p.m.
Created at: April 18, 2026, 2:14 a.m.