Triple
T4590737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis Vernon Harcourt |
E103480
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lewis |
E358648
|
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: Lewis | Statement: [Lewis Vernon Harcourt, givenName, Lewis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lewis Context triple: [Lewis Vernon Harcourt, givenName, Lewis]
-
A.
Lewis
"Lewis" is a notable film or television work featuring British actor Edward Fox, recognized as part of his distinguished acting career.
-
B.
Lewis
Lewis is a common English surname borne by numerous notable individuals across politics, civil rights, arts, and sports.
-
C.
Lewis
chosen
Lewis is a masculine given name of English origin, commonly used in English-speaking countries.
-
D.
Lee
Lee is a residential district in southeast London known for its suburban character, green spaces, and Victorian and Edwardian housing.
-
E.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5923c0c88190952137d448d474cf |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde0cdc7e8819088758c1d6d8e866d |
completed | March 21, 2026, 12:05 a.m. |
Created at: March 20, 2026, 1:11 p.m.