Triple
T9457392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Roe (DD-418) |
E228051
|
entity |
| Predicate | hasPennantType |
P89045
|
FINISHED |
| Object | destroyer hull classification symbol |
—
|
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: destroyer hull classification symbol | Statement: [USS Roe (DD-418), hasPennantType, destroyer hull classification symbol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPennantType Context triple: [USS Roe (DD-418), hasPennantType, destroyer hull classification symbol]
-
A.
pennantNumber
Indicates the identifying pennant number assigned to a ship or naval vessel.
-
B.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
C.
hasPantone
Indicates that one entity is associated with, or assigned, a specific Pantone color code.
-
D.
hasPocketType
Indicates the specific style or configuration of pocket associated with an item or garment.
-
E.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f90cf648190ab238ba6b4f03c4f |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69ccbf9b080c819098934a18cf2bac5d |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 7:52 p.m.