Triple

T24177757
Position Surface form Disambiguated ID Type / Status
Subject Larnaca Salt Lake E599329 entity
Predicate hasPart P35 FINISHED
Object Orphani Lake
Orphani Lake is one of the interconnected saline lakes that form part of the Larnaca Salt Lake complex near Larnaca, Cyprus.
E2274274 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: Orphani Lake | Statement: [Larnaca Salt Lake, hasPart, Orphani Lake]
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: Orphani Lake
Triple: [Larnaca Salt Lake, hasPart, Orphani Lake]
Generated description
Orphani Lake is one of the interconnected saline lakes that form part of the Larnaca Salt Lake complex near Larnaca, Cyprus.

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_69e288cca05481908faeb1563711114a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e1d24bec8190aab8d513c10e8210 completed April 29, 2026, 10:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41e006cf0c819081e9867caed221e3 completed June 29, 2026, 3:01 a.m.
NEDg Description generation batch_6a41e0dc929c8190ba87f8433ad2f9a4 completed June 29, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a41e1631740819093f8e3d82b8f8ac3 completed June 29, 2026, 3:07 a.m.
Created at: April 17, 2026, 11:34 p.m.