Triple
T9431274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Galatea |
E227379
|
entity |
| Predicate | mainCharacters |
P9202
|
FINISHED |
| Object | Leonida |
E368731
|
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: Leonida | Statement: [La Galatea, mainCharacters, Leonida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonida Context triple: [La Galatea, mainCharacters, Leonida]
-
A.
Leonida
chosen
Leonida is an Italian given name, historically used for both men and women and derived from the ancient Greek name Leonidas.
-
B.
Leonidaion
Leonidaion is an ancient guesthouse complex at Olympia in Greece, built in the 4th century BCE to accommodate distinguished visitors during the Olympic Games.
-
C.
Arsacia
Arsacia is an alternative name historically used for the city of Rayy (near modern-day Tehran) in ancient Persia.
-
D.
Leonidio
Leonidio is a traditional coastal town in the eastern Peloponnese of Greece, known for its dramatic red cliffs, Tsakonian cultural heritage, and popular rock-climbing routes.
-
E.
Corisande
Corisande is a noble lady and love interest in the medieval chivalric romance cycle "Amadis de Gaula."
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e5ed7408190beda5fb078e9345a |
completed | April 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1104033c08190a3670b017bd984d5 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:49 p.m.