Triple

T14925205
Position Surface form Disambiguated ID Type / Status
Subject Western Mongolia E371614 entity
Predicate hasLake P1025 FINISHED
Object Tolbo Lake
Tolbo Lake is a high-altitude freshwater lake in western Mongolia, known for its clear cold waters, surrounding mountain scenery, and historical significance as a 1921 battle site.
E1662227 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: Tolbo Lake | Statement: [Western Mongolia, hasLake, Tolbo 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: Tolbo Lake
Triple: [Western Mongolia, hasLake, Tolbo Lake]
Generated description
Tolbo Lake is a high-altitude freshwater lake in western Mongolia, known for its clear cold waters, surrounding mountain scenery, and historical significance as a 1921 battle 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_69d85cc7ea3481908228b5acb7d06f12 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded633da0c8190b39f606212e48e71 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10485ba70c819092ab75db8a67dceb completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a104a2a89e08190aa35e97ffb57fc9a completed May 22, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 10, 2026, 2:35 a.m.