Triple
T32623324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Junkers W 33 Bremen |
E833987
|
entity |
| Predicate | transatlanticCrossing |
P197989
|
FINISHED |
| Object | successful |
—
|
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: successful | Statement: [Junkers W 33 Bremen, transatlanticCrossing, successful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transatlanticCrossing Context triple: [Junkers W 33 Bremen, transatlanticCrossing, successful]
-
A.
totalTransatlanticCrossings
Indicates the number of times an entity has completed crossings across the Atlantic Ocean.
-
B.
crossesContinent
Indicates that one entity traverses from one side of a continent to the other, passing across its landmass.
-
C.
harbourCrossing
Indicates a relationship where one entity crosses or traverses a body of water via a harbour or designated harbour route.
-
D.
bodyOfWaterCrossedByFerry
Indicates that a body of water is traversed or crossed by a ferry service.
-
E.
firstNonStopTransatlanticFlightTo
Indicates that the subject entity completed the first non-stop transatlantic flight whose destination was the object entity.
- 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_69f3492ccc80819086ef7d26e9786647 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fec00f27988190955de6b6348a4d97 |
completed | May 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69febd52037c8190b475dbd50fdbc13e |
completed | May 9, 2026, 4:51 a.m. |
| PDg | Predicate description generation | batch_69fec00e5c1c819083d174bb4bc35f29 |
completed | May 9, 2026, 5:03 a.m. |
Created at: May 1, 2026, 1:06 a.m.