Triple
T26382026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saibai Island |
E663153
|
entity |
| Predicate | distanceToPapuaNewGuinea |
P196141
|
FINISHED |
| Object | a few kilometres |
—
|
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: a few kilometres | Statement: [Saibai Island, distanceToPapuaNewGuinea, a few kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPapuaNewGuinea Context triple: [Saibai Island, distanceToPapuaNewGuinea, a few kilometres]
-
A.
distanceToNewCaledonia
Indicates the measured or calculated distance between a given entity’s location and the location of New Caledonia.
-
B.
distanceFromTimor
Indicates the spatial distance between a given location and Timor.
-
C.
distanceToTorresStrait
Indicates the measured or specified distance between a given entity and the Torres Strait.
-
D.
distanceFromTongatapu
Indicates the measured distance between a given location and Tongatapu.
-
E.
distanceFromFijiMainlandKilometres
Indicates the distance, measured in kilometers, between an entity’s location and the mainland of Fiji.
- F. None of above. chosen
Provenance (4 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
| PDg | Predicate description generation | batch_69fe0d14778c8190986fa4f37f992a2f |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 26, 2026, 11:19 p.m.