Triple
T38606240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agona Swedru |
E934348
|
entity |
| Predicate | distanceToCapeCoast |
P206577
|
FINISHED |
| Object | approximately 60–70 km |
—
|
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: approximately 60–70 km | Statement: [Agona Swedru, distanceToCapeCoast, approximately 60–70 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCapeCoast Context triple: [Agona Swedru, distanceToCapeCoast, approximately 60–70 km]
-
A.
distanceToAccraApprox
Indicates an approximate distance between a given entity’s location and the city of Accra.
-
B.
distanceFromCaribbeanCoast
Indicates the measured distance between a location and the coastline of the Caribbean Sea.
-
C.
distanceFromCotonou
Indicates the measured spatial distance between a given location and the city of Cotonou.
-
D.
distanceToLomé
Indicates the spatial distance between a given entity or location and the city of Lomé.
-
E.
distanceToSekondi-Takoradi
Indicates the spatial distance between a given location and Sekondi-Takoradi.
- 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_69f76eccd6d081909ccce171011739a1 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c85e308819083dd67b96f457659 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:32 p.m.