Triple
T8313670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ides of March 44 BC |
E194650
|
entity |
| Predicate | hasApproximateNumberOfWounds |
P82703
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Ides of March 44 BC, hasApproximateNumberOfWounds, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfWounds Context triple: [Ides of March 44 BC, hasApproximateNumberOfWounds, 23]
-
A.
wasWoundedIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
-
B.
numberOfGunshotWounds
Indicates the count of gunshot wounds associated with a particular entity or event.
-
C.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
D.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
-
E.
killedOrMortallyWounded
Indicates that one entity caused the death of, or inflicted injuries certain to result in the death of, another entity.
- 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f5173c881909f2e84d53ea33a98 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bb3a708190bc705222092da614 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:55 p.m.