Triple
T30109483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miandrivazo |
E765224
|
entity |
| Predicate | distanceFromAntananarivo |
P202918
|
FINISHED |
| Object | approximately 400 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 400 km | Statement: [Miandrivazo, distanceFromAntananarivo, approximately 400 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromAntananarivo Context triple: [Miandrivazo, distanceFromAntananarivo, approximately 400 km]
-
A.
directionFromAntananarivo
Indicates the cardinal or relative direction in which one location lies when measured from Antananarivo.
-
B.
distanceFromMahé
Indicates the measured spatial distance between a given entity’s location and Mahé.
-
C.
distanceFromPortLouis
Indicates the measured distance between a given location and Port Louis.
-
D.
distanceToHoniaraApprox
Indicates an approximate distance measurement between a given entity’s location and the location of Honiara.
-
E.
distanceFromSihanoukville
Indicates the measured distance between a given location and Sihanoukville.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a00d08e8fac8190b59359134e6e1c03 |
completed | May 10, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_6a00d0127c088190a6f5b360450af113 |
completed | May 10, 2026, 6:36 p.m. |
| PDg | Predicate description generation | batch_6a00d08de20881908d83d98362e0751c |
completed | May 10, 2026, 6:38 p.m. |
Created at: April 29, 2026, 7:10 p.m.