Triple

T24159413
Position Surface form Disambiguated ID Type / Status
Subject Thanh Hoa Province E598787 entity
Predicate hasHistoricalSite P1098 FINISHED
Object Lam Kinh historical site
Lam Kinh historical site is a major Vietnamese heritage complex commemorating the Lam Sơn uprising and the early Lê dynasty, featuring royal tombs, temples, and ancient architectural remains.
E1622710 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: Lam Kinh historical site | Statement: [Thanh Hoa Province, hasHistoricalSite, Lam Kinh historical site]
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: Lam Kinh historical site
Triple: [Thanh Hoa Province, hasHistoricalSite, Lam Kinh historical site]
Generated description
Lam Kinh historical site is a major Vietnamese heritage complex commemorating the Lam Sơn uprising and the early Lê dynasty, featuring royal tombs, temples, and ancient architectural remains.

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_69e288cb0a3081909ef221744f274384 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e0e7f8e481909c55ae66bf7b16e9 completed April 29, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad33825c81909fa6f19be6d18ece completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae2d71448190b191a4877c698840 completed May 22, 2026, 1:15 a.m.
NED2 Entity disambiguation (via description) batch_6a0faefcb9048190abf1ccd608f1b607 completed May 22, 2026, 1:18 a.m.
Created at: April 17, 2026, 11:32 p.m.