Triple

T27797994
Position Surface form Disambiguated ID Type / Status
Subject Lhasa River E702167 entity
Predicate administrativeRegion P285 FINISHED
Object Chengguan District, Lhasa
Chengguan District, Lhasa is the central urban district and administrative, economic, and cultural heart of Lhasa, the capital of the Tibet Autonomous Region in China.
E1788346 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: Chengguan District, Lhasa | Statement: [Lhasa River, administrativeRegion, Chengguan District, Lhasa]
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: Chengguan District, Lhasa
Triple: [Lhasa River, administrativeRegion, Chengguan District, Lhasa]
Generated description
Chengguan District, Lhasa is the central urban district and administrative, economic, and cultural heart of Lhasa, the capital of the Tibet Autonomous Region in China.

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_69ef8408e0588190977cffa32dc33a29 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6380c776c8190afe636c9e65301a0 completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecd03d308190a2fd9d42bf261172 completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed8aade48190bbec489801889492 completed May 24, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee4f57508190aa0d1832b30a9556 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 5:32 p.m.