Triple
T2124525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finding Nemo |
E46396
|
entity |
| Predicate | character |
P662
|
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: [Finding Nemo, character, Nigel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nigel Context triple: [Finding Nemo, character, 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.
Thomas Nimely
Thomas Nimely is a Liberian politician and former rebel leader who headed the Movement for Democracy in Liberia (MODEL) during the Second Liberian Civil War and later served as Liberia’s foreign minister in the transitional government.
-
D.
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.
-
E.
Nigel Birch
Nigel Birch was a British Conservative politician and government minister who held several senior posts in the mid-20th century, including roles in economic and defense-related departments.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb55cb2c8190aab8199da3335032 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae519bfdb08190a7b715fbc5fd3f41 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:44 p.m.