Triple
T676640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Hornet (CV-8) |
E13091
|
entity |
| Predicate | sunk |
P17954
|
FINISHED |
| Object | 1942-10-27 |
—
|
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: 1942-10-27 | Statement: [USS Hornet (CV-8), sunk, 1942-10-27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sunk Context triple: [USS Hornet (CV-8), sunk, 1942-10-27]
-
A.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
B.
submerged
Indicates that one entity is located beneath the surface of a liquid or other surrounding medium, typically fully covered by it.
-
C.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
D.
shipwreckedOn
Indicates that an entity becomes stranded or marooned on a particular landmass or location as a result of a shipwreck.
-
E.
sunkCountry
Indicates that one entity (typically a vessel or force) caused the sinking of a country’s ship(s) or naval assets belonging to another country.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04b2ae881908a5c23453bef8572 |
completed | March 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69a49d1bbd0c81909cfbec30bd17bde7 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49ebf33c481909949526cb8f223dd |
completed | March 1, 2026, 8:17 p.m. |
Created at: March 1, 2026, 7:36 p.m.