Triple
T36348584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Sheffield (D80) |
E895131
|
entity |
| Predicate | pennantMarking |
P3153
|
FINISHED |
| Object | D80 |
—
|
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: D80 | Statement: [HMS Sheffield (D80), pennantMarking, D80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pennantMarking Context triple: [HMS Sheffield (D80), pennantMarking, D80]
-
A.
pennantNumber
chosen
Indicates the identifying pennant number assigned to a ship or naval vessel.
-
B.
billMarkings
Indicates a relationship where specific markings or patterns are present on or associated with a bill (such as a beak or financial document).
-
C.
aircraftMarking
Indicates a relationship where a marking, symbol, or identifier is applied to or displayed on an aircraft.
-
D.
coatMarkings
Indicates how an entity’s coat is patterned or marked, such as stripes, spots, or other distinctive visual markings.
-
E.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
- 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_69f76e4f437c8190a1af3ea2564f41f5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.