Triple
T19939925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ledra Palace crossing |
E479280
|
entity |
| Predicate | openedToCivilianCrossings |
P84489
|
FINISHED |
| Object | 2003 |
—
|
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: 2003 | Statement: [Ledra Palace crossing, openedToCivilianCrossings, 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedToCivilianCrossings Context triple: [Ledra Palace crossing, openedToCivilianCrossings, 2003]
-
A.
openedToCivilianTraffic
chosen
Indicates that a previously restricted or closed route, facility, or infrastructure has been made accessible for use by civilian (non-military) traffic.
-
B.
crossingOpened
Indicates that a crossing (such as a road, rail, or pedestrian crossing) has been opened or made available for passage.
-
C.
closedToCivilianTraffic
Indicates that access along a route or at a location is restricted so that civilian vehicles or pedestrians are not allowed to use it.
-
D.
openedToMilitaryTraffic
Indicates that a route, facility, or passage has been made accessible and available for use by military vehicles or operations.
-
E.
openedToPassengerTraffic
Indicates that a transportation facility or route began operating and accepting passengers for regular use.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a19d77c819088bce99c94568d0d |
completed | April 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.