Triple
T24938921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Cisterna |
E623392
|
entity |
| Predicate | RangerBattalionsLost |
P16565
|
FINISHED |
| Object | 1st 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: 1st Ranger Battalion | Statement: [Battle of Cisterna, RangerBattalionsLost, 1st Ranger Battalion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RangerBattalionsLost Context triple: [Battle of Cisterna, RangerBattalionsLost, 1st Ranger Battalion]
-
A.
numberOfBattalions
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
-
B.
hasBattalion
chosen
Indicates that one entity possesses, commands, or is organizationally assigned a specific battalion.
-
C.
orderOfBattle
Indicates the structured arrangement and hierarchical organization of military forces and units for a specific operation or engagement.
-
D.
UnionCorpsInvolved
Indicates that a Union military corps participated in or was involved in a specified event, operation, or engagement.
-
E.
hasBattalionNumber
Indicates that an entity (such as a military unit) is associated with a specific battalion number identifier.
- 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_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 5:30 a.m.