Triple
T2761466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Darwin |
E61228
|
entity |
| Predicate | distanceToAsia |
P6357
|
FINISHED |
| Object | closer to many Asian ports than southern Australian ports |
—
|
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: closer to many Asian ports than southern Australian ports | Statement: [Port of Darwin, distanceToAsia, closer to many Asian ports than southern Australian ports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAsia Context triple: [Port of Darwin, distanceToAsia, closer to many Asian ports than southern Australian ports]
-
A.
distanceToContinentApproximate
chosen
Indicates an approximate measure of how far something is from a specified continent.
-
B.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
C.
distanceToPacificOcean
Indicates the physical distance between a given location or entity and the Pacific Ocean.
-
D.
distanceToSouthAmerica
Indicates the spatial distance between a given entity’s location and the continent of South America.
-
E.
closestDistanceBetweenContinents
Indicates the minimum geographical distance separating any points on two different continents.
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.