Triple
T37692927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leopoldau extension |
E938853
|
entity |
| Predicate | hasNumberOfNewStations |
P183471
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Leopoldau extension, hasNumberOfNewStations, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfNewStations Context triple: [Leopoldau extension, hasNumberOfNewStations, 5]
-
A.
numberOfNewStations
chosen
Indicates the quantity of stations that are newly created, added, or introduced within a given context or time period.
-
B.
hasStations
Indicates that one entity possesses, contains, or is associated with one or more stations.
-
C.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
D.
hasGhostStations
Indicates that a transportation system or network includes disused, closed, or never-opened stations that still physically exist.
-
E.
hasDedicatedStations
Indicates that specific stations are exclusively assigned or reserved for a particular entity or purpose.
- 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
Created at: May 3, 2026, 4:18 p.m.