Triple
T19701698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Axe murder incident |
E473112
|
entity |
| Predicate | hasTypeOfTension |
P136995
|
FINISHED |
| Object | military standoff |
—
|
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: military standoff | Statement: [Axe murder incident, hasTypeOfTension, military standoff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfTension Context triple: [Axe murder incident, hasTypeOfTension, military standoff]
-
A.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
B.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
C.
strainType
Indicates the specific variety or subtype classification within a broader category of strains (e.g., biological, chemical, or product strains).
-
D.
hasStressSystem
Indicates that an entity possesses a particular system or pattern for assigning stress (emphasis) within its structure, such as in words or phrases.
-
E.
tensionArea
Indicates the region or extent over which mechanical or emotional tension is distributed or experienced.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b667908190841bb5fb7bfdb3f7 |
completed | April 20, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.