Triple
T24938923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Cisterna |
E623392
|
entity |
| Predicate | RangerBattalionsSeverelyMauled |
P42042
|
FINISHED |
| Object | 4th Ranger Battalion |
—
|
NE NERFINISHED |
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: 4th Ranger Battalion | Statement: [Battle of Cisterna, RangerBattalionsSeverelyMauled, 4th Ranger Battalion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RangerBattalionsSeverelyMauled Context triple: [Battle of Cisterna, RangerBattalionsSeverelyMauled, 4th Ranger Battalion]
-
A.
numberOfBattalions
chosen
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
-
B.
numberOfRegimentsInvolved
Indicates the total count of regiments that participated in or were involved in a specified event or action.
-
C.
armedConflictTheatre
Indicates a geographic area or location where an armed conflict takes place or is actively occurring.
-
D.
battleGroup
Indicates that multiple military units or forces are organized together as a single coordinated combat formation.
-
E.
isBattalionEquivalent
Indicates that one military unit has a size, role, or organizational status equivalent to that of a battalion.
- 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_69e2fac6b5a48190a1c38857f00915a9 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 5:30 a.m.