Triple
T4720462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Lashio |
E104751
|
entity |
| Predicate | effectOnInfrastructure |
P54339
|
FINISHED |
| Object | cutting of Burma Road |
—
|
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: cutting of Burma Road | Statement: [Battle of Lashio, effectOnInfrastructure, cutting of Burma Road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnInfrastructure Context triple: [Battle of Lashio, effectOnInfrastructure, cutting of Burma Road]
-
A.
infrastructureImpact
chosen
Indicates the effect that an action, event, or entity has on the condition, performance, or availability of infrastructure systems.
-
B.
infrastructureDamage
Indicates damage or destruction affecting physical infrastructure such as buildings, roads, utilities, or other constructed facilities.
-
C.
relatedInfrastructure
Indicates that one piece of infrastructure is connected, associated, or functionally related to another infrastructure element.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
isPartOfInfrastructure
Indicates that something belongs to, is included within, or functions as a component of a larger infrastructure system.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd680beb508190b3d74e20e1c64405 |
completed | March 20, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69bd621ddcd88190903288566f5e5dab |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.