Triple

T36062364
Position Surface form Disambiguated ID Type / Status
Subject Dzungarian Gate E1043121 entity
Predicate near P350 FINISHED
Object Lake Alakol
Lake Alakol is a large saline lake in eastern Kazakhstan, known for its biodiversity, therapeutic mineral waters, and importance as a stopover for migratory birds.
E2176347 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 Alakol | Statement: [Dzungarian Gate, near, Lake Alakol]
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 Alakol
Triple: [Dzungarian Gate, near, Lake Alakol]
Generated description
Lake Alakol is a large saline lake in eastern Kazakhstan, known for its biodiversity, therapeutic mineral waters, and importance as a stopover for migratory birds.

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_69f76e2f09448190b0486d5ecad5e243 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b2137e508190ba2fadbce32a2376 completed May 3, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a396df2d7a08190a543304a8915f6c0 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a3970311aa48190bc5c8424d2c9a4fc completed June 22, 2026, 5:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39708947fc819092e5a5bb24a3c288 completed June 22, 2026, 5:27 p.m.
Created at: May 3, 2026, 4:08 p.m.