Triple
T23197593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl of Leven |
E579916
|
entity |
| Predicate | notableFamilyName |
P18
|
FINISHED |
| Object | Leslie |
E26123
|
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: Leslie | Statement: [Earl of Leven, notableFamilyName, Leslie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leslie Context triple: [Earl of Leven, notableFamilyName, Leslie]
-
A.
Leslie
Leslie is the first name of Canadian singer-songwriter Feist, known for her indie pop music and distinctive vocal style.
-
B.
Leslie
Leslie is the given name of Sir Patrick Abercrombie, a prominent British town planner and architect known for his influential mid-20th-century urban plans.
-
C.
Leslie
Leslie is the given first name of American jazz pianist and vocalist Les McCann.
-
D.
Leslie
Leslie is the hapless, contract-bound protagonist of the dark British comedy film "Dead in a Week (Or Your Money Back)," whose attempts to end his life are complicated by an inept hitman.
-
E.
Leslie
chosen
Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1907770b48190a3194ecce9b45f09 |
completed | April 29, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f4bc9748190b1ab818a5171d03e |
completed | May 19, 2026, 10:45 a.m. |
Created at: April 17, 2026, 4:06 p.m.