Triple
T14816090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambalangoda |
E348318
|
entity |
| Predicate | distanceToGalle |
P112914
|
FINISHED |
| Object | approximately 25 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 25 km | Statement: [Ambalangoda, distanceToGalle, approximately 25 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGalle Context triple: [Ambalangoda, distanceToGalle, approximately 25 km]
-
A.
distanceFromGalle_km
chosen
Indicates the physical distance, measured in kilometers, between an entity and the location Galle.
-
B.
distanceToColombo
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Colombo.
-
C.
distanceToSriLanka
Indicates the spatial distance between a given entity’s location and the country of Sri Lanka.
-
D.
distanceFromGeorgeTown
Indicates the measured spatial distance between a given location and George Town.
-
E.
distanceToKandy_km
Indicates the physical distance, measured in kilometers, from a given location to Kandy.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe2c1ec81908b3dff7a5d0e85d0 |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:49 a.m.