Triple
T2688778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canterbury |
E57546
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Timaru |
E143237
|
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: Timaru | Statement: [Canterbury, containsCity, Timaru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timaru Context triple: [Canterbury, containsCity, Timaru]
-
A.
Timaru
chosen
Timaru is a coastal port town and service center on the east coast of New Zealand’s South Island.
-
B.
Waimate
Waimate is a small rural town in the South Island of New Zealand, known for its agricultural economy, historic buildings, and proximity to scenic natural landscapes.
-
C.
Palmerston North
Palmerston North is a major inland city in New Zealand known for its role as an educational and logistical hub, particularly home to Massey University.
-
D.
Tauranga
Tauranga is a major coastal city and port in the Bay of Plenty region of New Zealand, known for its beaches, harbor, and growing economic and tourism sectors.
-
E.
Otahuhu
Otahuhu is a suburb of Auckland, New Zealand, known for its strong Pacific Islander presence and vibrant Tongan community.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9f1ba3081909a349a2f30f8f9c9 |
completed | March 7, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa0741bc48190adffe6cfae831e26 |
completed | March 10, 2026, 4:39 a.m. |
Created at: March 6, 2026, 9:54 p.m.