Triple
T28176378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ploiești Nord railway station |
E715599
|
entity |
| Predicate | distanceToBucharestInKilometres |
P32714
|
FINISHED |
| Object | approximately 60 |
—
|
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 60 | Statement: [Ploiești Nord railway station, distanceToBucharestInKilometres, approximately 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBucharestInKilometres Context triple: [Ploiești Nord railway station, distanceToBucharestInKilometres, approximately 60]
-
A.
distanceToBucharest
chosen
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.
distanceToPloiești
Indicates the spatial distance between a given entity and the city of Ploiești.
-
D.
distanceFromAlbaIulia
Indicates the measured distance between a given place or entity and the location of Alba Iulia.
-
E.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
- F. None of above.
Provenance (3 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: April 27, 2026, 10:16 p.m.