Triple
T10903534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RMS Lusitania |
E257506
|
entity |
| Predicate | timeToSinkAfterTorpedo |
P96321
|
FINISHED |
| Object | about 18 minutes |
—
|
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: about 18 minutes | Statement: [RMS Lusitania, timeToSinkAfterTorpedo, about 18 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToSinkAfterTorpedo Context triple: [RMS Lusitania, timeToSinkAfterTorpedo, about 18 minutes]
-
A.
numberOfTorpedoesHit
Indicates the number of torpedoes that successfully struck a specified target.
-
B.
sunkAsTarget
Indicates that an entity was sunk specifically in the role of being a target (e.g., during testing, training, or as a deliberate target in an operation).
-
C.
dateHitByTorpedo
Indicates the specific date on which an entity was struck by a torpedo.
-
D.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
-
E.
torpedoed
Indicates that one entity attacked and struck another entity using a torpedo, typically causing damage or destruction.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a5dffc8190927b0928978646a4 |
completed | April 9, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101de31c819090707635f6790559 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:22 p.m.