Triple
T17915518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon |
E447914
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Levin |
—
|
NE NERFINISHED |
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: Levin | Statement: [Shannon, hasNearbyTown, Levin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levin Context triple: [Shannon, hasNearbyTown, Levin]
-
A.
Levin
Levin is a surname of Jewish origin borne by various notable individuals across fields such as business, politics, and the arts.
-
B.
Levin
chosen
Levin is a town in New Zealand’s North Island known as a service and retail hub for the surrounding agricultural Horowhenua district.
-
C.
Levin
Levin is a masculine given name of Germanic origin, historically borne by figures such as the Russian general Levin August von Bennigsen.
-
D.
Levshitz
Levshitz is an alternative transliteration of the Russian surname Lifshitz, commonly associated with several notable scientists and intellectuals.
-
E.
Lev
Lev is the Russian given name of the renowned writer Leo Tolstoy, under which he was known in his native language.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a3054f048190a98a3b314cd82d5c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 10:20 a.m.