Triple
T17238767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Slocum steamship disaster |
E418432
|
entity |
| Predicate | oneOfDeadliestMaritimeDisastersIn |
P126501
|
FINISHED |
| Object | United States history |
—
|
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: United States history | Statement: [General Slocum steamship disaster, oneOfDeadliestMaritimeDisastersIn, United States history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneOfDeadliestMaritimeDisastersIn Context triple: [General Slocum steamship disaster, oneOfDeadliestMaritimeDisastersIn, United States history]
-
A.
numberOfShipwrecks
Indicates the quantity of shipwrecks associated with a given entity or context.
-
B.
shipwrecksDestroyedIn
Indicates that one or more shipwrecks were destroyed within a specified location or during a particular event or time period.
-
C.
hasShipwrecks
Indicates that one entity contains, includes, or is associated with shipwrecks located within it or under its control.
-
D.
shipwreckEvent
Indicates an event in which a ship is destroyed, stranded, or severely damaged, typically resulting in loss or abandonment at sea or near a shoreline.
-
E.
sankOnMaidenVoyage
Indicates that the subject vessel sank during its very first voyage.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dfdc8688190aceb223c19a48781 |
completed | April 19, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:39 a.m.