Triple
T10542438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynda Resnick |
E248729
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Resnick |
E192958
|
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: Resnick | Statement: [Lynda Resnick, familyName, Resnick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Resnick Context triple: [Lynda Resnick, familyName, Resnick]
-
A.
Resnick
chosen
Resnick is a surname most notably associated with Mitchel Resnick, an influential researcher in learning sciences and creative technologies at the MIT Media Lab.
-
B.
Reznik
Reznik is a surname of likely Eastern European origin, often associated with Jewish and Slavic families and appearing in various transliterated forms such as Resnick.
-
C.
Rosenstein
Rosenstein is a surname most notably associated with Justin Rosenstein, the American software programmer and co-founder of Asana.
-
D.
Brisker
Brisker is a surname most notably associated with John Brisker, an American professional basketball player who mysteriously disappeared in the 1970s.
-
E.
Eisenberg
Eisenberg is a surname most notably associated with American actress Hallie Kate Eisenberg.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5190f46d08190a92b1191881ffb92 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9342e6cf48190b0ca53ff2a4e0214 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:32 p.m.