Triple
T6235978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Gravelines (1588) |
E139478
|
entity |
| Predicate | EnglishTactic |
P69683
|
FINISHED |
| Object | use of fireships to break Spanish crescent formation |
—
|
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: use of fireships to break Spanish crescent formation | Statement: [Battle of Gravelines (1588), EnglishTactic, use of fireships to break Spanish crescent formation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EnglishTactic Context triple: [Battle of Gravelines (1588), EnglishTactic, use of fireships to break Spanish crescent formation]
-
A.
EnglishCommander
Indicates that one entity serves as a military commander or leader for English forces in relation to another entity.
-
B.
englishFlagship
Indicates that an entity participates in or is associated with an English flagship program (typically an intensive, advanced English language or studies track).
-
C.
EnglishTranslation
Indicates that one expression is the English-language translation equivalent of another expression.
-
D.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062f236608190997e77b41095883f |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c05707d5408190a1d0fd80414ad957 |
completed | March 22, 2026, 8:54 p.m. |
Created at: March 22, 2026, 4:23 p.m.