Triple
T37201826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balchik Botanical Garden |
E922056
|
entity |
| Predicate | distanceToVarnaApproxKm |
P205779
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Balchik Botanical Garden, distanceToVarnaApproxKm, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVarnaApproxKm Context triple: [Balchik Botanical Garden, distanceToVarnaApproxKm, 40]
-
A.
distanceFromVarna
Indicates the measured or specified distance between a given entity and the location Varna.
-
B.
distanceToBurgas_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Burgas.
-
C.
distanceFromBlagoevgrad
Indicates the physical distance between a given entity or location and the city of Blagoevgrad.
-
D.
distanceFromStaraZagoraApproximateKm
Indicates the approximate distance, measured in kilometers, between an entity and Stara Zagora.
-
E.
distanceToPlovdiv
Indicates the spatial distance between a given entity and the city of Plovdiv.
- 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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:15 p.m.