Triple
T1738517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carnegie of Southesk |
E37974
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Carnegie |
E229
|
NE 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: Carnegie | Statement: [Carnegie of Southesk, familyName, Carnegie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carnegie Context triple: [Carnegie of Southesk, familyName, Carnegie]
-
A.
Carnegie
chosen
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
-
B.
Carnegie, Pennsylvania
Carnegie, Pennsylvania is a small borough in Allegheny County near Pittsburgh, historically tied to the region’s steel industry and local immigrant communities.
-
C.
Peabody
Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
-
D.
Bessemer
Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
-
E.
Bessemer
Bessemer is an industrial city in Jefferson County, Alabama, historically known for its steelmaking and manufacturing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63c35aec8190b5c19ace5524173f |
completed | March 6, 2026, 5:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8b03303c8190a301dca327bf9f47 |
completed | March 8, 2026, 2:43 p.m. |
Created at: March 4, 2026, 7:30 p.m.