Triple
T34949654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madura |
E1007953
|
entity |
| Predicate | distanceToBorderVillage_km |
P144927
|
FINISHED |
| Object | approximately 180 |
—
|
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 180 | Statement: [Madura, distanceToBorderVillage_km, approximately 180]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBorderVillage_km Context triple: [Madura, distanceToBorderVillage_km, approximately 180]
-
A.
distanceFromNearestSettlementKilometers
chosen
Indicates the distance, measured in kilometers, from an entity’s location to the closest human settlement.
-
B.
nearestIncorporatedVillage
Indicates that one place is the incorporated village geographically closest to another specified location.
-
C.
distanceToBorder
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
-
D.
administrativeCenterDistance
Indicates the distance between an entity and the administrative center that governs or represents it.
-
E.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.