Triple

T31700347
Position Surface form Disambiguated ID Type / Status
Subject Gulf of Tehuantepec E809037 entity
Predicate nearbyPort P5648 FINISHED
Object Puerto Chiapas
Puerto Chiapas is a commercial and cruise port in the southern Mexican state of Chiapas on the Pacific coast, serving as a regional hub for maritime trade and tourism near the Guatemalan border.
E1973484 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: Puerto Chiapas | Statement: [Gulf of Tehuantepec, nearbyPort, 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: Puerto Chiapas
Triple: [Gulf of Tehuantepec, nearbyPort, Puerto Chiapas]
Generated description
Puerto Chiapas is a commercial and cruise port in the southern Mexican state of Chiapas on the Pacific coast, serving as a regional hub for maritime trade and tourism near the Guatemalan border.

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_69f348de914081909fc8edff56f34dbe completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aaa9a1e08190b15b6a5f4986e755 completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84c9fea48190bcdc6472b698b1d0 completed June 12, 2026, 4:02 a.m.
NEDg Description generation batch_6a2b8590d4f48190b126ede3e93631b9 completed June 12, 2026, 4:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2b85fe65348190801652c66bb72cf9 completed June 12, 2026, 4:07 a.m.
Created at: April 30, 2026, 11:11 p.m.