Triple
T14681874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LZ 129 Hindenburg |
E344805
|
entity |
| Predicate | totalTransatlanticCrossings |
P115305
|
FINISHED |
| Object | 63 |
—
|
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: 63 | Statement: [LZ 129 Hindenburg, totalTransatlanticCrossings, 63]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalTransatlanticCrossings Context triple: [LZ 129 Hindenburg, totalTransatlanticCrossings, 63]
-
A.
crossesContinent
Indicates that one entity traverses from one side of a continent to the other, passing across its landmass.
-
B.
firstNonStopTransatlanticFlightTo
Indicates that the subject entity completed the first non-stop transatlantic flight whose destination was the object entity.
-
C.
numberOfVoyagesToAmericas
Indicates the count of distinct voyages an entity has made to the Americas.
-
D.
firstNonStopTransatlanticFlightDate
Indicates the date on which an entity completed its first nonstop flight across the Atlantic Ocean.
-
E.
firstNonStopTransatlanticFlightFrom
Indicates that the subject is the origin location of the first non-stop transatlantic flight associated with the object.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56a51ec8190941684fd562a7182 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:28 a.m.