Triple
T10903561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sinking of the RMS Lusitania |
E257507
|
entity |
| Predicate | numberOfTorpedoesFired |
P96322
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [sinking of the RMS Lusitania, numberOfTorpedoesFired, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTorpedoesFired Context triple: [sinking of the RMS Lusitania, numberOfTorpedoesFired, 1]
-
A.
numberOfTorpedoesHit
Indicates the number of torpedoes that successfully struck a specified target.
-
B.
numberOfTorpedoTubes
Indicates the quantity of torpedo tubes associated with or installed on an entity.
-
C.
armamentTorpedoes
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
D.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
-
E.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
- 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.