Triple
T556990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Riverina |
E11962
|
entity |
| Predicate | includesTown |
P847
|
FINISHED |
| Object |
Harden
Harden is a small rural town in the Riverina region of New South Wales, Australia, known historically as a railway and agricultural service centre.
|
E69894
|
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: Harden | Statement: [Division of Riverina, includesTown, Harden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harden Context triple: [Division of Riverina, includesTown, Harden]
-
A.
Aldridge
Aldridge is an English-origin surname borne by various notable individuals in fields such as sports, entertainment, and the arts.
-
B.
Bryant
Bryant is the middle name of James B. Conant, the influential American chemist, educator, and president of Harvard University.
-
C.
Durant
Durant is a surname most famously associated with William C. Durant, the pioneering American automobile magnate who co-founded General Motors.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
The Hoops
The Hoops is a common nickname for FC Dallas, a professional Major League Soccer club based in the Dallas–Fort Worth metroplex.
- 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: Harden Triple: [Division of Riverina, includesTown, Harden]
Generated description
Harden is a small rural town in the Riverina region of New South Wales, Australia, known historically as a railway and agricultural service centre.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harden Target entity description: Harden is a small rural town in the Riverina region of New South Wales, Australia, known historically as a railway and agricultural service centre.
-
A.
Aldridge
Aldridge is an English-origin surname borne by various notable individuals in fields such as sports, entertainment, and the arts.
-
B.
Bryant
Bryant is the middle name of James B. Conant, the influential American chemist, educator, and president of Harvard University.
-
C.
Durant
Durant is a surname most famously associated with William C. Durant, the pioneering American automobile magnate who co-founded General Motors.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
The Hoops
The Hoops is a common nickname for FC Dallas, a professional Major League Soccer club based in the Dallas–Fort Worth metroplex.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d28af148190acad3cfb809ff2f2 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4e644f41c819099743a6c4f2815e4 |
completed | March 2, 2026, 1:22 a.m. |
| NEDg | Description generation | batch_69a4e6cfdbf48190814dfb9d2bd8dbf5 |
completed | March 2, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4e79f2a8881909210998edba8a2a8 |
completed | March 2, 2026, 1:27 a.m. |
Created at: March 1, 2026, 7:32 p.m.