Triple
T12803070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Franklin |
E306072
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Samuel |
E18206
|
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: Samuel | Statement: [Samuel Franklin, givenName, Samuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samuel Context triple: [Samuel Franklin, givenName, Samuel]
-
A.
Samuel
Samuel is the birth name of the famed American author Mark Twain, known for classics like "The Adventures of Tom Sawyer" and "Adventures of Huckleberry Finn."
-
B.
Samuel
chosen
Samuel is a masculine given name of Hebrew origin meaning "name of God" or "God has heard," widely used across many cultures and languages.
-
C.
Benjamin
Benjamin is the naive, dream-filled protagonist of Mendele Mocher Sforim’s satirical Yiddish novel "The Travels of Benjamin the Third," often likened to a Jewish Don Quixote.
-
D.
Benjamin
Benjamin is the given first name of Australian actor Ben Mendelsohn, known for his versatile roles in film and television.
-
E.
Benjamin
Benjamin is the given first name of the American film producer and studio executive B. P. Schulberg.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7e3be48190ba9159c9f1ac2ccd |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ec463f08190822e5235362cf584 |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:30 p.m.