Triple
T1079228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robben Island |
E23909
|
entity |
| Predicate | distanceFromCapeTown |
P23676
|
FINISHED |
| Object | about 6.9 kilometers |
—
|
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 6.9 kilometers | Statement: [Robben Island, distanceFromCapeTown, about 6.9 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCapeTown Context triple: [Robben Island, distanceFromCapeTown, about 6.9 kilometers]
-
A.
distanceToSouthAfrica
Indicates the measured or calculated spatial distance between a given entity and the country of South Africa.
-
B.
Port of Durban
Indicates a relationship where something is located at, associated with, or operating through the Port of Durban as a maritime transport or logistics hub.
-
C.
distanceFromSouthPole
Indicates the measured distance of an entity from the geographic South Pole.
-
D.
distanceFromJuanFernandezIslands_km
Indicates the distance, measured in kilometers, between an entity and the Juan Fernández Islands.
-
E.
distanceToSaintHelena
Indicates the measured distance between a given entity and the location of Saint Helena.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b943b41481909b24050ca7e78971 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.