Triple
T31624200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Savannah (CL-42) |
E806976
|
entity |
| Predicate | placeOfDamage |
P87330
|
FINISHED |
| Object | off Salerno, Italy |
—
|
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: off Salerno, Italy | Statement: [USS Savannah (CL-42), placeOfDamage, off Salerno, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeOfDamage Context triple: [USS Savannah (CL-42), placeOfDamage, off Salerno, Italy]
-
A.
notableLocationOfDamage
chosen
Indicates the specific place where damage is prominently present or has significantly occurred.
-
B.
damagedIn
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
C.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
D.
sufferedDamageTo
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
E.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
- F. None of above.
Provenance (3 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_69f348d7883c8190b6c13ab92b7ef076 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: April 30, 2026, 10:42 p.m.