Triple

T16502319
Position Surface form Disambiguated ID Type / Status
Subject Chợ Lớn E400827 entity
Predicate languageUsed P238 FINISHED
Object Hokkien E410805 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: Hokkien | Statement: [Chợ Lớn, languageUsed, Hokkien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hokkien
Context triple: [Chợ Lớn, languageUsed, Hokkien]
  • A. Hokkien chosen
    Hokkien is a Southern Min Chinese language variety widely spoken in Taiwan, Southeast Asia, and parts of southern China, known for its rich tonal system and distinct vocabulary from Mandarin.
  • B. Hongū
    Hongū is the principal sanctuary building of Tsurugaoka Hachimangū Shrine in Kamakura, serving as its main place of worship and ritual.
  • C. Nanbu
    Nanbu is a town in Shizuoka Prefecture, Japan, known for its rural landscape and location near the border with Yamanashi Prefecture.
  • D. Kahama
    Kahama is a town and district-level administrative center in northwestern Tanzania known for its mining activities and role as a commercial hub in the Shinyanga area.
  • E. Nanyō
    Nanyō is a city in Yamagata Prefecture, Japan, known for its hot springs, cherry orchards, and traditional festivals.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e50436c8190836a1bc2baa188b1 completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582e6e288190825af8758097e325 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:14 a.m.