Triple
T24278816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2004 Krue Se Mosque incident |
E605482
|
entity |
| Predicate | hasInsurgentsArmament |
P155645
|
FINISHED |
| Object | small arms |
—
|
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: small arms | Statement: [2004 Krue Se Mosque incident, hasInsurgentsArmament, small arms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInsurgentsArmament Context triple: [2004 Krue Se Mosque incident, hasInsurgentsArmament, small arms]
-
A.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
-
B.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
-
C.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
-
D.
armamentStatus
Indicates the current condition or readiness level of an entity’s weapons or military equipment.
-
E.
armedVariants
Indicates that one entity is a version or model of another that is equipped with weapons or enhanced armaments.
- 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f5032f48190a027e2d8b382ee79 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:07 a.m.