Triple
T23497074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Business Services |
E571730
|
entity |
| Predicate | offersSecurityService |
P17471
|
FINISHED |
| Object | managed security services |
—
|
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: managed security services | Statement: [Orange Business Services, offersSecurityService, managed security services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersSecurityService Context triple: [Orange Business Services, offersSecurityService, managed security services]
-
A.
offersServiceIn
Indicates that a provider makes a particular service available within a specified location or jurisdiction.
-
B.
offersServiceTo
Indicates that one entity provides or makes a service available for the benefit or use of another entity.
-
C.
offersServiceOn
Indicates that one entity provides or makes a service available on, during, or through another entity (such as a platform, date, or location).
-
D.
offersServiceType
chosen
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
E.
securityGuarantee
Indicates a commitment by one party to protect or defend another party against specified threats or risks.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7e0c5a48190badb8303f40f6180 |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:05 p.m.