Triple
T1477782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Gravelines |
E30881
|
entity |
| Predicate | englishCasualties |
P10775
|
FINISHED |
| Object | relatively light |
—
|
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: relatively light | Statement: [Battle of Gravelines, englishCasualties, relatively light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: englishCasualties Context triple: [Battle of Gravelines, englishCasualties, relatively light]
-
A.
casualtiesUKKilled
Indicates that the relationship specifies the number of people from the UK who were killed in the referenced event or incident.
-
B.
casualtiesAllied
Indicates the number or extent of losses (killed, wounded, or missing) suffered by allied forces in a conflict or incident.
-
C.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
D.
casualtiesDescription
chosen
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
E.
casualtiesBritishWounded
Indicates the number of British individuals who were wounded as a result of a specific event or action.
- 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.