Triple
T12314972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokoroa |
E293576
|
entity |
| Predicate | distanceTo Hamilton (approx km) |
P95530
|
FINISHED |
| Object | 90 |
—
|
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: 90 | Statement: [Tokoroa, distanceTo Hamilton (approx km), 90]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceTo Hamilton (approx km) Context triple: [Tokoroa, distanceTo Hamilton (approx km), 90]
-
A.
distanceFromHamilton
chosen
Indicates the spatial distance between a given entity and the location identified as Hamilton.
-
B.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
C.
distanceToOttawaByRoad
Indicates the length of the travel route between a place and Ottawa when moving along the road network rather than in a straight line.
-
D.
distanceFromVictoria
Indicates the measured distance between a given entity or location and Victoria.
-
E.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.