Triple

T36188581
Position Surface form Disambiguated ID Type / Status
Subject Lake Mahalona E1046918 entity
Predicate partOf P40 FINISHED
Object Sulawesi lake system
The Sulawesi lake system is a connected group of tectonic and rift lakes on the Indonesian island of Sulawesi, noted for their unique endemic aquatic biodiversity and complex hydrological links.
E2173248 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: Sulawesi lake system | Statement: [Lake Mahalona, partOf, Sulawesi lake system]
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: Sulawesi lake system
Triple: [Lake Mahalona, partOf, Sulawesi lake system]
Generated description
The Sulawesi lake system is a connected group of tectonic and rift lakes on the Indonesian island of Sulawesi, noted for their unique endemic aquatic biodiversity and complex hydrological links.

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_69f76e3d4fbc81908c159c7beeb4ce00 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b51662048190ab92048453eaa652 completed May 3, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a393413ed1881909c12a3fedebc6a25 completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a3935f970a48190aca3e12b7a728e74 completed June 22, 2026, 1:17 p.m.
NED2 Entity disambiguation (via description) batch_6a393680f0f881908d48fdb70d7bd4d2 completed June 22, 2026, 1:20 p.m.
Created at: May 3, 2026, 4:08 p.m.