Triple
T3869443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samtredia |
E91945
|
entity |
| Predicate | distanceFromKutaisi_km |
P46936
|
FINISHED |
| Object | ~25 |
—
|
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: ~25 | Statement: [Samtredia, distanceFromKutaisi_km, ~25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKutaisi_km Context triple: [Samtredia, distanceFromKutaisi_km, ~25]
-
A.
distanceFromKutaisi
chosen
Indicates the spatial distance measured from the location of Kutaisi to another specified place or entity.
-
B.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
-
C.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
D.
distanceFromYerevan_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Yerevan.
-
E.
distanceFromSamarkand_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Samarkand.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec533828819080f52dae15fdbecd |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.