Triple
T10603511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Świna |
E275811
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Swine |
E275811
|
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: Swine | Statement: [Świna, hasGermanName, Swine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swine Context triple: [Świna, hasGermanName, Swine]
-
A.
Świna
chosen
Świna is a strait in the Baltic Sea region that connects the Szczecin Lagoon with the Pomeranian Bay, separating parts of the islands of Usedom and Wolin in northwestern Poland.
-
B.
Sus scrofa
Sus scrofa is the wild boar, a widespread Eurasian mammal that is the wild ancestor of the domestic pig.
-
C.
Pig
Pig is a 2021 neo-noir drama film starring Nicolas Cage as a reclusive truffle hunter searching for his stolen foraging pig.
-
D.
Porcile
Porcile is a 1969 Italian film by Pier Paolo Pasolini that blends dark satire and allegory to critique bourgeois morality and authoritarian power.
-
E.
PIG
PIG is the commonly used acronym for Pine Island Glacier, one of Antarctica’s largest and fastest-changing glaciers, significant for its impact on global sea-level rise.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded6d698819084f96f46ea941461 |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eaffcd0819098e0a06a731b602f |
completed | April 10, 2026, 8:33 p.m. |
Created at: April 8, 2026, 7:32 p.m.