Triple
T35349676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eraclea |
E1020841
|
entity |
| Predicate | distanceToCaorleByRoad_km |
P206946
|
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: [Eraclea, distanceToCaorleByRoad_km, approximately 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCaorleByRoad_km Context triple: [Eraclea, distanceToCaorleByRoad_km, approximately 20]
-
A.
distanceToVenice_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Venice.
-
B.
distanceToPistoia_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Pistoia.
-
C.
distanceToSavona_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Savona.
-
D.
distanceToBrindisi
Indicates the measured or specified distance between a given entity or location and the city of Brindisi.
-
E.
distanceToTrieste
Indicates the measured or calculated distance between a given entity or location and the city of Trieste.
- 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_69f76decd95c8190ae428f6a19d535de |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.