Triple
T1312483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North East England |
E28023
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Mackem
Mackem is a regional English dialect and associated identity from the Sunderland area of North East England.
|
E149817
|
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: Mackem | Statement: [North East England, hasDialect, Mackem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mackem Context triple: [North East England, hasDialect, Mackem]
-
A.
Hackett
Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
-
B.
Hucknall
Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
-
C.
Mott
Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
-
D.
Mackmen
The Mackmen was a nickname for the early 20th-century Philadelphia Athletics baseball team, derived from their legendary manager Connie Mack.
-
E.
Short Brothers
Short Brothers is a historic British aerospace company best known as one of the world’s first aircraft manufacturers and a pioneer in early aviation and flying boat design.
- 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: Mackem Triple: [North East England, hasDialect, Mackem]
Generated description
Mackem is a regional English dialect and associated identity from the Sunderland area of North East England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mackem Target entity description: Mackem is a regional English dialect and associated identity from the Sunderland area of North East England.
-
A.
Hackett
Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
-
B.
Hucknall
Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
-
C.
Mott
Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
-
D.
Mackmen
The Mackmen was a nickname for the early 20th-century Philadelphia Athletics baseball team, derived from their legendary manager Connie Mack.
-
E.
Short Brothers
Short Brothers is a historic British aerospace company best known as one of the world’s first aircraft manufacturers and a pioneer in early aviation and flying boat design.
- 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1572b1c8190ab978198c2d655c8 |
completed | March 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbaeeece08190a805a2f037e709ce |
completed | March 7, 2026, 11:55 p.m. |
| NEDg | Description generation | batch_69acbb74a0e48190b2018b16363afea1 |
completed | March 7, 2026, 11:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69acbbcd8c1c8190b58680d7a1ecd982 |
completed | March 7, 2026, 11:59 p.m. |
Created at: March 1, 2026, 7:55 p.m.