Triple
T13415670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary |
E313204
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Sarkology |
E304097
|
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: Sarkology | Statement: [Mary, follows, Sarkology]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarkology Context triple: [Mary, follows, Sarkology]
-
A.
Sarkology
chosen
Sarkology is a studio album by Ghanaian rapper Sarkodie that showcases his blend of hip hop and Afrobeats and helped solidify his status in African music.
-
B.
End of the World Museum
End of the World Museum is a regional history museum in Ushuaia, Argentina, showcasing the natural, cultural, and maritime heritage of Tierra del Fuego and the southernmost regions of the world.
-
C.
Stone Zoo
Stone Zoo is a medium-sized zoological park in Stoneham, Massachusetts, featuring a variety of animal exhibits and family-oriented educational programs.
-
D.
Panoptikum wax museum
Panoptikum wax museum is a historic wax museum in Hamburg, Germany, known for its lifelike figures of celebrities, historical personalities, and cultural icons.
-
E.
Whatizit
Whatizit is a text-mining web service developed by the European Bioinformatics Institute for automatically identifying and annotating biological terms in scientific text.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb6e904819098cc9153fd2feaf5 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7308095548190afb659b84f2775f2 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:39 p.m.