Triple
T10088915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satan Met a Lady |
E215290
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Kenneth |
E561889
|
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: Kenneth | Statement: [Satan Met a Lady, character, Kenneth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenneth Context triple: [Satan Met a Lady, character, Kenneth]
-
A.
Kenneth
Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
-
B.
Kenneth
Kenneth is the full given name of American documentary filmmaker Ken Burns, renowned for his in-depth historical films and distinctive storytelling style.
-
C.
Kenneth
chosen
Kenneth is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
D.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
E.
Edwin
Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd057e32881908bf630559af94906 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b693afac819090635d2eb147bdcb |
completed | April 5, 2026, 7:22 p.m. |
Created at: March 30, 2026, 9:01 p.m.