Triple

T35069309
Position Surface form Disambiguated ID Type / Status
Subject Butrint Lake E1011821 entity
Predicate hasAlternativeName P39 FINISHED
Object Lake Butrint
Lake Butrint is a coastal lagoon in southern Albania, known for its rich biodiversity and proximity to the ancient archaeological site of Butrint, a UNESCO World Heritage Site.
E2124319 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: Lake Butrint | Statement: [Butrint Lake, hasAlternativeName, Lake Butrint]
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: Lake Butrint
Triple: [Butrint Lake, hasAlternativeName, Lake Butrint]
Generated description
Lake Butrint is a coastal lagoon in southern Albania, known for its rich biodiversity and proximity to the ancient archaeological site of Butrint, a UNESCO World Heritage Site.

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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7861a3eb481909f9bd86edbbc3947 completed May 3, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c644b54c819099cc2301dac88f6e completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c704e7c88190a1e12c6aa9375992 completed June 21, 2026, 11:12 a.m.
NED2 Entity disambiguation (via description) batch_6a37c82ccd3c8190ac151138acfa58df completed June 21, 2026, 11:17 a.m.
Created at: May 3, 2026, 4:01 p.m.