Triple
T504494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenrothes (UK Parliament constituency) |
E10473
|
entity |
| Predicate | containsTown |
P847
|
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: [Glenrothes (UK Parliament constituency), containsTown, Leslie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leslie Context triple: [Glenrothes (UK Parliament constituency), containsTown, Leslie]
-
A.
Leslie
chosen
Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
-
B.
Nance
Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
C.
Lester
Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
-
D.
Lester
Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
-
E.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f149bd1c81908ff58ac504ace2bf |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56c475ce88190bf16e5ee76f1d3b5 |
completed | March 2, 2026, 10:53 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.