Triple

T28271245
Position Surface form Disambiguated ID Type / Status
Subject Jardines de la Reina E712858 entity
Predicate hasSpecies P965 FINISHED
Object Goliath grouper
The Goliath grouper is a massive, slow-growing reef fish of the Atlantic and Caribbean known for its enormous size, booming vocalizations, and preference for wrecks and coral structures.
E1814368 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: Goliath grouper | Statement: [Jardines de la Reina, hasSpecies, Goliath grouper]
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: Goliath grouper
Triple: [Jardines de la Reina, hasSpecies, Goliath grouper]
Generated description
The Goliath grouper is a massive, slow-growing reef fish of the Atlantic and Caribbean known for its enormous size, booming vocalizations, and preference for wrecks and coral structures.

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_69efb5216c6881908020dce4aea65381 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f64447b738819088589cca5312c4e8 completed May 2, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627a1305881908f5a42c2ad4cf37e completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a1628d2b46081909fdfefd0a41a19b1 completed May 26, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_6a16294f42508190aac4e3617131dafe completed May 26, 2026, 11:14 p.m.
Created at: April 27, 2026, 11:17 p.m.