Triple
T8912176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Somme 1916 |
E212209
|
entity |
| Predicate | firstDayCasualties |
P35438
|
FINISHED |
| Object | approximately 57,000 British casualties |
—
|
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: approximately 57,000 British casualties | Statement: [Somme 1916, firstDayCasualties, approximately 57,000 British casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstDayCasualties Context triple: [Somme 1916, firstDayCasualties, approximately 57,000 British casualties]
-
A.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
B.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
C.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
D.
casualtiesAssociatedWithEvent
chosen
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
-
E.
englishCasualtiesKilledAndWounded
Indicates the number of English individuals who were either killed or wounded as a result of a particular event or conflict.
- 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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6525d1408190a76522d7c4ac37da |
completed | April 1, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:56 p.m.