Triple
T2528187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lungga River |
E56087
|
entity |
| Predicate | nearbyMilitaryOperations |
P21619
|
FINISHED |
| Object | Allied operations on Guadalcanal |
—
|
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: Allied operations on Guadalcanal | Statement: [Lungga River, nearbyMilitaryOperations, Allied operations on Guadalcanal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyMilitaryOperations Context triple: [Lungga River, nearbyMilitaryOperations, Allied operations on Guadalcanal]
-
A.
militaryActivity
Indicates that an entity is engaged in, associated with, or affected by actions, operations, or preparations conducted by armed forces.
-
B.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
C.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
D.
nearbyBattlefield
chosen
Indicates that one entity is located close to or in the immediate vicinity of a battlefield.
-
E.
hasNearbyMilitaryTrainingArea
Indicates that an entity is located close to a designated area used for military training activities.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd257ea908190a010c0b785853546 |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.