Triple
T8256166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vagharshapat |
E193074
|
entity |
| Predicate | distanceToYerevan_km |
P43261
|
FINISHED |
| Object | approximately 20 |
—
|
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 20 | Statement: [Vagharshapat, distanceToYerevan_km, approximately 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToYerevan_km Context triple: [Vagharshapat, distanceToYerevan_km, approximately 20]
-
A.
distanceFromYerevan_km
chosen
Indicates the physical distance, measured in kilometers, between a given place and the city of Yerevan.
-
B.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
-
C.
distanceFromAkhaltsikhe_km
Indicates the distance, measured in kilometers, between an entity and the location of Akhaltsikhe.
-
D.
distanceFromAshgabat
Indicates the measured spatial distance between a given location and the city of Ashgabat.
-
E.
distanceToKutaisi_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Kutaisi.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78fb91d08190904c59ccc0cd444a |
completed | March 31, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69cb36b6d5548190b665a6cce14c69f7 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:49 p.m.