Triple
T25830096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Counter Sniper Team |
E650637
|
entity |
| Predicate | typicalDeploymentLocation |
P21833
|
FINISHED |
| Object | rooftops |
—
|
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: rooftops | Statement: [Counter Sniper Team, typicalDeploymentLocation, rooftops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDeploymentLocation Context triple: [Counter Sniper Team, typicalDeploymentLocation, rooftops]
-
A.
typicalDeployment
Indicates that one entity represents the standard or most commonly used deployment configuration or pattern for the other entity.
-
B.
deploymentLocation
Indicates the place or environment where something (such as a system, resource, or component) is deployed or put into operational use.
-
C.
typicalUseLocation
chosen
Indicates the usual or most common location where an entity is used or operates.
-
D.
firstLargeDeploymentLocation
Indicates the location where something (such as a system, product, or technology) was first deployed at large scale.
-
E.
geographicDeployment
Indicates how something is distributed, implemented, or present across different geographic locations or regions.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 22, 2026, 7:38 a.m.