Triple
T2866034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlington Arcade |
E63439
|
entity |
| Predicate | securityStaffType |
P11881
|
FINISHED |
| Object | beadles |
—
|
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: beadles | Statement: [Burlington Arcade, securityStaffType, beadles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: securityStaffType Context triple: [Burlington Arcade, securityStaffType, beadles]
-
A.
personnelType
chosen
Indicates the classification or role category assigned to a person within an organization or system.
-
B.
securityType
Indicates the classification or category of security associated with an entity, such as the type of financial instrument, protection mechanism, or access control applied.
-
C.
securityOrganizationMembership
Indicates that an entity is a member of, or affiliated with, a particular security-related organization or body.
-
D.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
E.
personnelComposition
Indicates the makeup or distribution of people or roles within a group, organization, or unit.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfbb7ed4819096ca65391077e2af |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.