Triple
T28904844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London, Airstrip One |
E733043
|
entity |
| Predicate | surveillanceLevel |
P147440
|
FINISHED |
| Object | ubiquitous |
—
|
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: ubiquitous | Statement: [London, Airstrip One, surveillanceLevel, ubiquitous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surveillanceLevel Context triple: [London, Airstrip One, surveillanceLevel, ubiquitous]
-
A.
surveillanceStrengthenedDuring
Indicates that surveillance measures were intensified or reinforced during a specified time period or event.
-
B.
surveillanceCondition
chosen
Indicates the specific circumstances or criteria under which surveillance or monitoring of an entity is required, active, or applicable.
-
C.
exposureLevel
Indicates the degree or intensity to which an entity is subjected or exposed to a particular factor, condition, or influence.
-
D.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
-
E.
activationLevel
Indicates the degree or intensity to which something is currently active, engaged, or functioning within a given context.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:06 a.m.