Triple
T4031217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watertown, Massachusetts shootout |
E83713
|
entity |
| Predicate | hasLawEnforcementResponse |
P18305
|
FINISHED |
| Object | deployment of tactical units |
—
|
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: deployment of tactical units | Statement: [Watertown, Massachusetts shootout, hasLawEnforcementResponse, deployment of tactical units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawEnforcementResponse Context triple: [Watertown, Massachusetts shootout, hasLawEnforcementResponse, deployment of tactical units]
-
A.
lawEnforcementResponse
chosen
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
-
B.
lawEnforcementStatus
Indicates the relationship between an entity and its current standing or condition with respect to law enforcement, such as being under investigation, wanted, detained, or cleared.
-
C.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
D.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
-
E.
usedByLawEnforcementModel
Indicates that something is employed or utilized by law enforcement agencies or personnel, typically as a tool, method, or model in their operations or decision-making.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb0dbb8481909ff2ee49dadcd1dc |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.