Triple
T6890102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogor |
E159022
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Rain City |
E159022
|
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: Rain City | Statement: [Bogor, nickname, Rain City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rain City Context triple: [Bogor, nickname, Rain City]
-
A.
Rain City
chosen
Rain City is the popular nickname of Bogor, an Indonesian city renowned for its frequent rainfall and cool, lush climate.
-
B.
Rain City
Rain City is a popular nickname for Vancouver, a coastal Canadian city known for its frequent rainfall and lush, temperate climate.
-
C.
Waterfall City
Waterfall City is a large, modern mixed-use commercial and residential development in Midrand, South Africa, known for its corporate offices, retail centers, and contemporary urban planning.
-
D.
Cream City
Cream City is a nickname for Milwaukee, Wisconsin, derived from the distinctive light-colored cream brick used in many of its historic buildings.
-
E.
Queen City
Queen City is the common nickname for Manchester, the largest city in New Hampshire and a historic center of industry and commerce in the state.
- 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_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d92d45f08190a730b3842c95b521 |
completed | March 27, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748d16e5c81909e35db99af5cfa51 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:23 p.m.