Triple
T1958105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenifer Lewis |
E42315
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lewis |
E104439
|
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: [Jenifer Lewis, familyName, Lewis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lewis Context triple: [Jenifer Lewis, familyName, 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
chosen
Lewis is a common English surname borne by numerous notable individuals across politics, civil rights, arts, and sports.
-
C.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
D.
Willard
Willard is a masculine given name of Old English origin meaning "resolute" or "strong-willed."
-
E.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb37e21cc8190b6e13b86bc93d594 |
completed | March 7, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbcc9ba48190985f48dbef1f2d94 |
completed | March 8, 2026, 10:44 p.m. |
Created at: March 4, 2026, 7:36 p.m.