Triple

T27797978
Position Surface form Disambiguated ID Type / Status
Subject Lhasa River E702167 entity
Predicate hasBridge P386 FINISHED
Object Liuwu Bridge
Liuwu Bridge is a major road bridge in Lhasa, Tibet, that connects central Lhasa with the Liuwu New District across the Lhasa River.
E1791866 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: Liuwu Bridge | Statement: [Lhasa River, hasBridge, Liuwu Bridge]
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: Liuwu Bridge
Triple: [Lhasa River, hasBridge, Liuwu Bridge]
Generated description
Liuwu Bridge is a major road bridge in Lhasa, Tibet, that connects central Lhasa with the Liuwu New District across the Lhasa River.

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_6a12f71c568c8190b343b55aa7916c07 completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12fb496c188190abbbcd5200aa5457 completed May 24, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbc87d94819097dbb89898b6ba03 completed May 24, 2026, 1:23 p.m.
Created at: April 27, 2026, 5:32 p.m.