Triple
T11161202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navassa Island |
E264039
|
entity |
| Predicate | distanceToJamaica |
P98176
|
FINISHED |
| Object | about 160 kilometers northeast of Jamaica |
—
|
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: about 160 kilometers northeast of Jamaica | Statement: [Navassa Island, distanceToJamaica, about 160 kilometers northeast of Jamaica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToJamaica Context triple: [Navassa Island, distanceToJamaica, about 160 kilometers northeast of Jamaica]
-
A.
distanceToHavana
Indicates the measured spatial distance between a given entity’s location and the city of Havana.
-
B.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
C.
distanceFromCharlotteAmalie
Indicates the measured distance between a given location and Charlotte Amalie.
-
D.
distanceFromMiami
Indicates the spatial distance between a given entity’s location and the city of Miami.
-
E.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8817a90819087820d5241c58851 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.