Triple
T28265200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azuga |
E712682
|
entity |
| Predicate | distanceFromBrașov |
P201179
|
FINISHED |
| Object | approximately 35 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: approximately 35 kilometres | Statement: [Azuga, distanceFromBrașov, approximately 35 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBrașov Context triple: [Azuga, distanceFromBrașov, approximately 35 kilometres]
-
A.
distanceToBucharest
Indicates the physical distance between a given location and the city of Bucharest.
-
B.
distanceToCraiova_km
Indicates the physical distance, measured in kilometers, between a given entity and the city of Craiova.
-
C.
distanceToBacău
Indicates the spatial distance between a given entity and the location of Bacău.
-
D.
distanceToPloiești
Indicates the spatial distance between a given entity and the city of Ploiești.
-
E.
distanceFromAlbaIulia
Indicates the measured distance between a given place or entity and the location of Alba Iulia.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69ffdd0486e08190a0f2ff4ce0aee13b |
completed | May 10, 2026, 1:19 a.m. |
Created at: April 27, 2026, 11:14 p.m.