Triple
T32007578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Mayrant (DD-402) |
E817311
|
entity |
| Predicate | locationOfMajorDamage |
P87330
|
FINISHED |
| Object | off Palermo, Sicily |
—
|
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 Palermo, Sicily | Statement: [USS Mayrant (DD-402), locationOfMajorDamage, off Palermo, Sicily]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfMajorDamage Context triple: [USS Mayrant (DD-402), locationOfMajorDamage, off Palermo, Sicily]
-
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.
isMajorDamOf
Indicates that one dam is the primary or most significant dam associated with a particular river, reservoir, or water system.
-
D.
wasHeavilyDamagedOn
Indicates that an entity experienced severe damage at or during a specified time or event.
-
E.
damagedBy
Indicates that one entity has caused harm, impairment, 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0204dafcc08190868a6f3eab162505 |
completed | May 11, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a0202dc60348190a140bb9da906f5b6 |
completed | May 11, 2026, 4:25 p.m. |
Created at: May 1, 2026, 12:15 a.m.