Triple
T14007860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Insular Chile |
E336996
|
entity |
| Predicate | distanceFromSouthAmerica |
P15349
|
FINISHED |
| Object | hundreds of kilometers west of Chilean coast |
—
|
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: hundreds of kilometers west of Chilean coast | Statement: [Insular Chile, distanceFromSouthAmerica, hundreds of kilometers west of Chilean coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSouthAmerica Context triple: [Insular Chile, distanceFromSouthAmerica, hundreds of kilometers west of Chilean coast]
-
A.
distanceToSouthAmerica
chosen
Indicates the spatial distance between a given entity’s location and the continent of South America.
-
B.
distanceFromCentralAmerica
Indicates the measured spatial distance between a given entity and the region of Central America.
-
C.
distanceToContinentApproximate
Indicates an approximate measure of how far something is from a specified continent.
-
D.
distanceFromSouthPole
Indicates the measured distance of an entity from the geographic South Pole.
-
E.
distanceFromBuenosAires
Indicates the measured distance between a given entity’s location and the city of Buenos Aires.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed327d88190a53af5768468a8eb |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.