Triple

T11535505
Position Surface form Disambiguated ID Type / Status
Subject Johann Schreck E273535 entity
Predicate workLocation P7 FINISHED
Object Macao E7092 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: Macao | Statement: [Johann Schreck, workLocation, Macao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macao
Context triple: [Johann Schreck, workLocation, Macao]
  • A. Macau chosen
    Macau is a Special Administrative Region of China known for its blend of Portuguese and Chinese cultures and its major casino and tourism industry.
  • B. Macau
    Macau is a coastal municipality in the Brazilian state of Rio Grande do Norte, known for its salt production and fishing activities.
  • C. Hong Kong, China
    Hong Kong, China is a major global financial and trading hub and a Special Administrative Region of China located on the southern coast of the country.
  • D. Magong
    Magong is the main urban center and largest city of Taiwan’s Penghu (Pescadores) archipelago, serving as its political, economic, and transportation hub.
  • E. Macau Peninsula
    Macau Peninsula is the historic urban core of Macau, known for its dense casino district, colonial Portuguese architecture, and role as the region’s main commercial and tourism hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e7137a09608190801af2125e2e8095 completed April 21, 2026, 6:04 a.m.
Created at: April 8, 2026, 9:37 p.m.