Triple
T1696718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigel Farage |
E36674
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nigel |
E107138
|
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: Nigel | Statement: [Nigel Farage, givenName, Nigel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nigel Context triple: [Nigel Farage, givenName, Nigel]
-
A.
Nigel
chosen
Nigel is a masculine given name of English origin, historically derived from the Latin name Nigellus and commonly used in the UK and other English-speaking countries.
-
B.
Colin
Colin is a masculine given name of Irish and Scottish origin, commonly used in English-speaking countries.
-
C.
Nigel Holmes
Nigel Holmes is a British-born graphic designer and information graphics specialist known for his influential work in explanatory and data visualization design.
-
D.
Reginald
Reginald is a masculine given name of English origin that has been borne by various notable figures, including military officers, politicians, and artists.
-
E.
Cecil
Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b78d20819096f0602058c46d8a |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad799ad838819087e945f47284a3b0 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:30 p.m.