Triple

T37649668
Position Surface form Disambiguated ID Type / Status
Subject Saser Kangri I E937135 entity
Predicate nearbyGlacier P4580 FINISHED
Object Saser Glacier
Saser Glacier is a high-altitude mountain glacier in the eastern Karakoram range of Ladakh, India, known for its proximity to the Saser Kangri massif and its role in feeding local river systems.
E2291663 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: Saser Glacier | Statement: [Saser Kangri I, nearbyGlacier, Saser Glacier]
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: Saser Glacier
Triple: [Saser Kangri I, nearbyGlacier, Saser Glacier]
Generated description
Saser Glacier is a high-altitude mountain glacier in the eastern Karakoram range of Ladakh, India, known for its proximity to the Saser Kangri massif and its role in feeding local river systems.

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_69f76ed4fe908190b8061c5c135e0971 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba989336c8190b4d957c00cd566aa completed May 6, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c7a6a3a14819082084d287c1f3ea9 completed July 19, 2026, 7:19 a.m.
NEDg Description generation batch_6a5c7b069228819080c6ef4ffcf0c6d3 completed July 19, 2026, 7:21 a.m.
NED2 Entity disambiguation (via description) batch_6a5c7b57e6d881908ea86041e7fbfa8e completed July 19, 2026, 7:23 a.m.
Created at: May 3, 2026, 4:18 p.m.