Triple
T6041365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Wakatipu |
E134551
|
entity |
| Predicate | rankByLengthInNewZealand |
P55219
|
FINISHED |
| Object | longest lake in New Zealand |
—
|
LITERAL 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: longest lake in New Zealand | Statement: [Lake Wakatipu, rankByLengthInNewZealand, longest lake in New Zealand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByLengthInNewZealand Context triple: [Lake Wakatipu, rankByLengthInNewZealand, longest lake in New Zealand]
-
A.
lengthRankingInNewZealand
chosen
Indicates the relative ordering of entities based on their length specifically within the context of New Zealand.
-
B.
rankInSizeInNewZealandIslands
Indicates the ordinal position of an island in New Zealand when ordered by size (e.g., largest, second largest, etc.).
-
C.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
D.
rankByLength
Indicates ordering a set of items based on their length, typically from shortest to longest or vice versa.
-
E.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
- F. None of above.
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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056d11370819096ac35349bd91f4e |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:08 p.m.