Triple
T34214448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vatican City railway station |
E877746
|
entity |
| Predicate | hasLengthOfRailwayWithinVatican |
P77732
|
FINISHED |
| Object | approximately 300 metres |
—
|
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 300 metres | Statement: [Vatican City railway station, hasLengthOfRailwayWithinVatican, approximately 300 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthOfRailwayWithinVatican Context triple: [Vatican City railway station, hasLengthOfRailwayWithinVatican, approximately 300 metres]
-
A.
railwayNetworkLength
Indicates the total measured length of all railway tracks within a specified railway network.
-
B.
papalNunciatureLocatedIn
Indicates that a papal nunciature (the diplomatic mission of the Holy See) is situated within a specific geographic or political location.
-
C.
railwayLineLength
chosen
Indicates the total measured length of a railway line.
-
D.
supremePontiffResidence
Indicates the residence associated with the supreme pontiff (e.g., where the supreme pontiff officially lives or is based).
-
E.
hasRingRoadLengthApproxKm
Indicates that an entity has a ring road whose length is approximately a specified number of kilometers.
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:55 a.m.