Triple
T25124632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen Light Rail |
E629362
|
entity |
| Predicate | airportSectionOpened |
P157949
|
FINISHED |
| Object | 2017-04-22 |
—
|
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: 2017-04-22 | Statement: [Bergen Light Rail, airportSectionOpened, 2017-04-22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportSectionOpened Context triple: [Bergen Light Rail, airportSectionOpened, 2017-04-22]
-
A.
airportOpened
Indicates that an airport began operations or was officially opened at a specific time.
-
B.
openedAsPartOfAirport
Indicates that something was opened concurrently with, or as an integral component of, the opening of an airport.
-
C.
openedAsCivilAirport
Indicates that a facility or location began operation specifically as a civil (non-military) airport.
-
D.
airportFeature
Indicates that an airport possesses or is characterized by a particular feature, facility, or attribute.
-
E.
openedAirportBranch
Indicates that an entity established and began operating a branch or location at an airport.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f465cf077c819091cdefb28f4a35d2 |
completed | May 1, 2026, 8:35 a.m. |
| PD | Predicate disambiguation | batch_69f44d8043b081908bbffd7f044b4f26 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 18, 2026, 6:28 a.m.