Triple

T34782895
Position Surface form Disambiguated ID Type / Status
Subject Mexican Pacific Islands E1002720 entity
Predicate hasPart P35 FINISHED
Object Isla San Benito
Isla San Benito is a small, remote island off the Pacific coast of Baja California, Mexico, known for its rugged terrain, rich marine life, and important seabird colonies.
E2173357 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: Isla San Benito | Statement: [Mexican Pacific Islands, hasPart, Isla San Benito]
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: Isla San Benito
Triple: [Mexican Pacific Islands, hasPart, Isla San Benito]
Generated description
Isla San Benito is a small, remote island off the Pacific coast of Baja California, Mexico, known for its rugged terrain, rich marine life, and important seabird colonies.

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_69f76db47d408190a24fc7164439ea2d completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a5bce8c8190b9435e9953889448 completed May 3, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3933e71ad48190a31c8a6ada1c5c71 completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a393551ea208190a075eb301aa99bc7 completed June 22, 2026, 1:14 p.m.
NED2 Entity disambiguation (via description) batch_6a3935ed3c3c8190bf17fe2eb6eb45d4 completed June 22, 2026, 1:17 p.m.
Created at: May 3, 2026, 3:59 p.m.