Triple
T18301826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FRAD |
E438374
|
entity |
| Predicate | hasEntityType |
P16808
|
FINISHED |
| Object |
Agency
An agency is an organization or business that provides specific services or acts on behalf of others, often within governmental, commercial, or creative sectors.
|
E1317535
|
NE FINISHED |
How this triple was built (4 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: Agency | Statement: [FRAD, hasEntityType, Agency]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agency Context triple: [FRAD, hasEntityType, Agency]
-
A.
Benefits Agency
The Benefits Agency was a UK government executive agency responsible for administering social security benefits to the public.
-
B.
Delegate
Delegate is a small rural town in the Snowy Monaro region of New South Wales, Australia, known for its historic buildings and proximity to the New South Wales–Victoria border.
-
C.
United Agents
United Agents is a prominent London-based talent agency representing actors, writers, directors, and other creatives across film, television, theatre, and publishing.
-
D.
ACY
ACY is the three-letter IATA airport code for Atlantic City International Airport in New Jersey, USA.
-
E.
Superagent
Superagent is a film featuring Ojani Noa, known for his work as an actor and former spouse of Jennifer Lopez.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Agency Triple: [FRAD, hasEntityType, Agency]
Generated description
An agency is an organization or business that provides specific services or acts on behalf of others, often within governmental, commercial, or creative sectors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Agency Target entity description: An agency is an organization or business that provides specific services or acts on behalf of others, often within governmental, commercial, or creative sectors.
-
A.
Benefits Agency
The Benefits Agency was a UK government executive agency responsible for administering social security benefits to the public.
-
B.
Delegate
Delegate is a small rural town in the Snowy Monaro region of New South Wales, Australia, known for its historic buildings and proximity to the New South Wales–Victoria border.
-
C.
United Agents
United Agents is a prominent London-based talent agency representing actors, writers, directors, and other creatives across film, television, theatre, and publishing.
-
D.
ACY
ACY is the three-letter IATA airport code for Atlantic City International Airport in New Jersey, USA.
-
E.
Superagent
Superagent is a film featuring Ojani Noa, known for his work as an actor and former spouse of Jennifer Lopez.
- F. None of above. chosen
Provenance (5 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50180ac48819090e9a8f11ba10c3d |
completed | April 19, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03bb5e1fb481908a0b98ea130eda71 |
completed | May 12, 2026, 11:44 p.m. |
| NEDg | Description generation | batch_6a03bdb3fb3c819095192ac49e809f55 |
completed | May 12, 2026, 11:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03c193a0a08190b33d80d45f3ed0f0 |
completed | May 13, 2026, 12:10 a.m. |
Created at: April 10, 2026, 10:35 a.m.