Triple
T6243247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirta |
E139653
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Myrtle |
E532007
|
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: Myrtle | Statement: [Mirta, relatedName, Myrtle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myrtle Context triple: [Mirta, relatedName, Myrtle]
-
A.
Myrtle
chosen
Myrtle is a fictional character appearing in P. G. Wodehouse’s comic novel "Service with a Smile."
-
B.
Melaleuca
Melaleuca is a genus of flowering plants in the myrtle family, best known for species like the tea tree that produce aromatic oils used in medicine and cosmetics.
-
C.
Palmetto
Palmetto is a long-distance Amtrak passenger train service operating along the U.S. East Coast between New York City and Savannah, Georgia.
-
D.
DeBary
DeBary is a small city in central Florida known as a residential community along the St. Johns River in Volusia County.
-
E.
Myrties
Myrties is a coastal village on the Greek island of Kalymnos, known for its beach, views of the islet Telendos, and role as a base for climbers and tourists.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631b32308190a8211043d1caa6e6 |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20e0d62208190928bab473ca64417 |
completed | March 24, 2026, 4:07 a.m. |
Created at: March 22, 2026, 4:23 p.m.