Triple
T1477784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Gravelines |
E30881
|
entity |
| Predicate | spanishShipsLostOrDamaged |
P821
|
FINISHED |
| Object | many ships damaged or rendered unseaworthy |
—
|
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: many ships damaged or rendered unseaworthy | Statement: [Battle of Gravelines, spanishShipsLostOrDamaged, many ships damaged or rendered unseaworthy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spanishShipsLostOrDamaged Context triple: [Battle of Gravelines, spanishShipsLostOrDamaged, many ships damaged or rendered unseaworthy]
-
A.
shipsSunkOrTotalLoss
chosen
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
B.
notableShip
Indicates that there is a notable or significant ship associated with the subject entity.
-
C.
battleshipsDamaged
Indicates that one or more battleships have sustained damage, typically as a result of combat or hostile action.
-
D.
capturedShip
Indicates that one party has taken control of another party's ship, typically by force or seizure.
-
E.
survivingShipsOfFleet
Indicates the subset of ships from a given fleet that remain operational or undestroyed after a specific event or period.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c605d4c0819088ab06678b2ba6f3 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c484e52c81908948ff8c0a42751b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:11 p.m.