Triple
T14190409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahlon Sweet |
E351696
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mahlon |
E111242
|
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: Mahlon | Statement: [Mahlon Sweet, givenName, Mahlon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahlon Context triple: [Mahlon Sweet, givenName, Mahlon]
-
A.
Mahlon
chosen
Mahlon is a minor biblical figure in the Book of Ruth, known as one of Naomi’s sons and the first husband of Ruth.
-
B.
Dedan
Dedan is a biblical figure mentioned in the Hebrew Bible as a descendant of Abraham through Keturah and associated with an Arabian tribe or region known for trade.
-
C.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
D.
Pangborn
Pangborn is a surname most notably associated with American character actor Franklin Pangborn, known for his comedic roles in early 20th-century films.
-
E.
Sylvanus
Sylvanus is the full given name of Canadian ice hockey legend Syl Apps, a Hall of Fame center known for his career with the Toronto Maple Leafs.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61df628c8190ba3f557e2128dce5 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd194543f081909cb11cf0881afa90 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:03 a.m.