Triple
T9541123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airborne Stand-Off Radar |
E230158
|
entity |
| Predicate | surveillanceDomain |
P60634
|
FINISHED |
| Object | land battlefield |
—
|
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: land battlefield | Statement: [Airborne Stand-Off Radar, surveillanceDomain, land battlefield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surveillanceDomain Context triple: [Airborne Stand-Off Radar, surveillanceDomain, land battlefield]
-
A.
domainServed
chosen
Indicates that a particular domain or area is supported, covered, or provided for by a given entity or service.
-
B.
containsDomain
Indicates that one entity includes or encompasses a specific domain as part of its scope, structure, or area of applicability.
-
C.
inputDomain
Indicates that a function, process, or system accepts inputs belonging to a specified domain or set of allowable values.
-
D.
typicalDomain
Indicates that one entity is the characteristic or most common domain, context, or area of application in which another entity typically occurs or is used.
-
E.
monitoredFor
Indicates that one entity is being observed or tracked over time to detect, assess, or manage the occurrence or progression of another entity (such as a condition, event, or risk).
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.