Triple
T11977883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John G. Kemeny |
E285081
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kemeny |
E592488
|
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: Kemeny | Statement: [John G. Kemeny, familyName, Kemeny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kemeny Context triple: [John G. Kemeny, familyName, Kemeny]
-
A.
Kemeny
chosen
Kemeny is a surname most notably associated with figures such as mathematician and computer scientist John G. Kemeny, co-developer of the BASIC programming language and former president of Dartmouth College.
-
B.
Tilden
Tilden is a given name and surname most notably associated with several prominent American figures in politics, sports, and the arts.
-
C.
Karlin
Karlin is the professional stage name used by Danish songwriter and producer Kenneth Karlin, known for his work in pop and R&B music.
-
D.
Karlin
Karlin is a historic Hasidic dynasty and Jewish community that originated in the town of Karlin, now a district of Pinsk in Belarus.
-
E.
Ervin
Ervin is a masculine given name of Germanic origin, closely related to names like Erwin and Irvin.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90393cfb08190b5b45d3e5e32fad3 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471f6afc48190856a0f7c486b28aa |
completed | May 1, 2026, 9:27 a.m. |
Created at: April 8, 2026, 9:46 p.m.