Triple
T11696033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marine City |
E277995
|
entity |
| Predicate | hasNearbyAttraction |
P2064
|
FINISHED |
| Object | Centum City |
E157613
|
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: Centum City | Statement: [Marine City, hasNearbyAttraction, Centum City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Centum City Context triple: [Marine City, hasNearbyAttraction, Centum City]
-
A.
Centum City
chosen
Centum City is a major modern business and entertainment district in Busan, South Korea, known for its high-rise complexes, shopping centers, and cultural venues.
-
B.
Mima City
Mima City is a municipality in western Tokushima Prefecture, Japan, known for its historic townscapes, traditional indigo dyeing culture, and scenic rural landscapes.
-
C.
Shannon City
Shannon City is a small rural community in southern Iowa, United States.
-
D.
Virgil City
Virgil City is a small unincorporated community located in Missouri, United States.
-
E.
Daye City
Daye City is a county-level city in southeastern Hubei Province, China, known historically for its rich mineral resources and metal mining industry.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.