Triple
T31407119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kandahar–Herat Highway |
E801159
|
entity |
| Predicate | conditionIssues |
P172228
|
FINISHED |
| Object | security-related damage |
—
|
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: security-related damage | Statement: [Kandahar–Herat Highway, conditionIssues, security-related damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionIssues Context triple: [Kandahar–Herat Highway, conditionIssues, security-related damage]
-
A.
conditions
Indicates that one entity specifies or imposes requirements, constraints, or circumstances that must be satisfied or hold true for another entity or situation.
-
B.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
C.
hadMultipleIssues
Indicates that the subject experienced more than one problem, error, or issue in the relevant context.
-
D.
structuralIssues
Indicates that there are problems or deficiencies in the design, construction, or integrity of a structure or system.
-
E.
underlyingIssue
Indicates that one situation, problem, or condition is the fundamental cause or root problem behind another.
- 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_69f348c0dd648190bf2fd7642f78eb06 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a915ead881909463ae46419c343e |
completed | May 3, 2026, 1:47 a.m. |
Created at: April 30, 2026, 8:33 p.m.