Triple
T9093444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Eylau |
E217948
|
entity |
| Predicate | casualtiesCharacter |
P10775
|
FINISHED |
| Object | disproportionately high relative to territorial gains |
—
|
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: disproportionately high relative to territorial gains | Statement: [Battle of Eylau, casualtiesCharacter, disproportionately high relative to territorial gains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesCharacter Context triple: [Battle of Eylau, casualtiesCharacter, disproportionately high relative to territorial gains]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
casualtiesType
Indicates the specific category or nature of casualties (e.g., killed, injured, missing) associated with an event or incident.
-
C.
casualtiesDescription
chosen
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
D.
crewFatality
Indicates that one or more members of a crew have died as a result of the related event or situation.
-
E.
casualtiesAssociatedWithEvent
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b347d4819085b33d0e20834f47 |
completed | April 1, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:14 p.m.