Triple

T38003652
Position Surface form Disambiguated ID Type / Status
Subject Macuspana Municipality E948171 entity
Predicate hasRiver P165 FINISHED
Object Puxcatán River
The Puxcatán River is a regional waterway in the Mexican state of Tabasco that flows through Macuspana Municipality and contributes to its local hydrology and ecosystems.
E2285204 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: Puxcatán River | Statement: [Macuspana Municipality, hasRiver, Puxcatán River]
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: Puxcatán River
Triple: [Macuspana Municipality, hasRiver, Puxcatán River]
Generated description
The Puxcatán River is a regional waterway in the Mexican state of Tabasco that flows through Macuspana Municipality and contributes to its local hydrology and ecosystems.

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_69f76efb4b10819092c8c2ba28ac06a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc93e31308190a4ce6a3f4060ea76 completed May 6, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a450309f71081908ae3ac5e363e08e4 completed July 1, 2026, 12:07 p.m.
NEDg Description generation batch_6a4503fea7dc8190b3411d48d1dcc12f completed July 1, 2026, 12:11 p.m.
NED2 Entity disambiguation (via description) batch_6a45383b64d481908f6199fb264086b7 completed July 1, 2026, 3:54 p.m.
Created at: May 3, 2026, 4:20 p.m.