Triple
T13591141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iruppu Falls |
E324693
|
entity |
| Predicate | distanceFromMadikeri |
P110203
|
FINISHED |
| Object | about 80 kilometres |
—
|
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 80 kilometres | Statement: [Iruppu Falls, distanceFromMadikeri, about 80 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMadikeri Context triple: [Iruppu Falls, distanceFromMadikeri, about 80 kilometres]
-
A.
distanceFromMysuru
Indicates the spatial distance between a given location and the city of Mysuru.
-
B.
distanceFromBengaluru
Indicates the measured spatial distance between a given entity’s location and the city of Bengaluru.
-
C.
distanceFromBangalore
Indicates the spatial distance separating a given entity or location from Bangalore.
-
D.
distanceToHyderabad
Indicates the spatial distance between a given entity’s location and the city of Hyderabad.
-
E.
distanceToKohima_km
Indicates the physical distance, measured in kilometers, from a given entity or location to Kohima.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.