Triple
T23844569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INSAS family of small arms |
E591083
|
entity |
| Predicate | reliabilityIssuesReported |
P21734
|
FINISHED |
| Object | magazine cracking in cold weather |
—
|
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: magazine cracking in cold weather | Statement: [INSAS family of small arms, reliabilityIssuesReported, magazine cracking in cold weather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reliabilityIssuesReported Context triple: [INSAS family of small arms, reliabilityIssuesReported, magazine cracking in cold weather]
-
A.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
-
C.
knownIssue
chosen
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
-
D.
hadIssue
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
E.
facingIssue
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c88a4b948190989a261e79b996a6 |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:09 p.m.