Triple
T18247803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodbe Monastery |
E436998
|
entity |
| Predicate | distanceToSighnaghi |
P131017
|
FINISHED |
| Object | approximately 2 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 2 km | Statement: [Bodbe Monastery, distanceToSighnaghi, approximately 2 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSighnaghi Context triple: [Bodbe Monastery, distanceToSighnaghi, approximately 2 km]
-
A.
distanceFromAkhaltsikhe_km
Indicates the distance, measured in kilometers, between an entity and the location of Akhaltsikhe.
-
B.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
-
C.
distanceFromKutaisi
Indicates the spatial distance measured from the location of Kutaisi to another specified place or entity.
-
D.
distanceToKutaisi_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Kutaisi.
-
E.
distanceFromMestia
Indicates the spatial distance between a given place and the location of Mestia.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e89b288190a286797ec2cd60a8 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:33 a.m.