Triple
T20049917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whangārei District |
E499165
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kamo |
—
|
NE NERFINISHED |
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: Kamo | Statement: [Whangārei District, contains, Kamo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamo Context triple: [Whangārei District, contains, Kamo]
-
A.
Kamo
Kamo was a former town in Japan’s Kyoto Prefecture that was once part of Soraku District before being merged into a larger municipality.
-
B.
Kamo
Kamo is a city in central Niigata Prefecture, Japan, known for its scenic rural landscapes and traditional local industries.
-
C.
Kamo
chosen
Kamo is a residential suburb and community located just north of central Whangārei in New Zealand’s Northland Region.
-
D.
Kamo
Kamo is a rural village located in Armenia’s Shirak Province.
-
E.
Tenryū
Tenryū is a guardian statue associated with the famous Kaminarimon gate at Sensō-ji Temple in Tokyo, representing a protective dragon deity in Japanese Buddhist tradition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:37 p.m.