Triple
T1418667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silchar |
E31972
|
entity |
| Predicate | distanceToBangladeshBorder_km |
P27554
|
FINISHED |
| Object | approximately 35 |
—
|
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 35 | Statement: [Silchar, distanceToBangladeshBorder_km, approximately 35]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBangladeshBorder_km Context triple: [Silchar, distanceToBangladeshBorder_km, approximately 35]
-
A.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
B.
distanceFromKolkata
Indicates the spatial distance between a given location and the city of Kolkata.
-
C.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
-
D.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
E.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c40631e881909ddf81a2eb84af1c |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:59 p.m.