Triple

T26867608
Position Surface form Disambiguated ID Type / Status
Subject Humla–Purang border crossing E676517 entity
Predicate connects P390 FINISHED
Object Purang County
Purang County is a remote county in southwestern Tibet, China, situated near the borders with Nepal and India and known as a key Himalayan trade and pilgrimage gateway.
E1743815 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: Purang County | Statement: [Humla–Purang border crossing, connects, Purang County]
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: Purang County
Triple: [Humla–Purang border crossing, connects, Purang County]
Generated description
Purang County is a remote county in southwestern Tibet, China, situated near the borders with Nepal and India and known as a key Himalayan trade and pilgrimage gateway.

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_69eee9ba94bc8190b44c5d4397d04ecd completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61e98eb7881909d8b323c85ec787f completed May 2, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12135c0a9481909e4681600ea8ef4d completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a12144d20688190a5a89c747a90c7a1 completed May 23, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a12150ca50881909438084adda62d39 completed May 23, 2026, 8:58 p.m.
Created at: April 27, 2026, 5:29 a.m.