Triple
T5372200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Šabac |
E108876
|
entity |
| Predicate | distanceToBelgrade |
P63607
|
FINISHED |
| Object | approximately 90 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 90 km | Statement: [Šabac, distanceToBelgrade, approximately 90 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBelgrade Context triple: [Šabac, distanceToBelgrade, approximately 90 km]
-
A.
distanceToTirana_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Tirana.
-
B.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
C.
distanceToBucharest
Indicates the physical distance between a given location and the city of Bucharest.
-
D.
distanceFromLjubljana
Indicates the spatial distance between an entity and the city of Ljubljana.
-
E.
distanceToŽilina_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Žilina.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd88801b188190b9ac35ed89167fa3 |
completed | March 20, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69bd846172788190969f24bc7503c05e |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd887f5b0081909456992d1a071928 |
completed | March 20, 2026, 5:48 p.m. |
Created at: March 20, 2026, 2:02 p.m.