Triple
T4379565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veria |
E99094
|
entity |
| Predicate | distanceFromThessaloniki |
P56484
|
FINISHED |
| Object | approximately 70 km southwest |
—
|
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 70 km southwest | Statement: [Veria, distanceFromThessaloniki, approximately 70 km southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromThessaloniki Context triple: [Veria, distanceFromThessaloniki, approximately 70 km southwest]
-
A.
distanceFromHeraklion
Indicates the spatial distance between a given location and the city of Heraklion.
-
B.
distanceFromMiletus
Indicates the spatial distance between a given place or object and the location of Miletus.
-
C.
distanceToBucharest
Indicates the physical distance between a given location and the city of Bucharest.
-
D.
rankByAreaInGreece
Indicates the relative ordering of entities based on their area size within the geographic boundaries of Greece.
-
E.
distanceToBlackSea
Indicates the measured spatial distance between a given entity and the Black Sea.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3524154dc81908532cdf997dcb802 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.