Triple
T16600636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latin League |
E403320
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Aricia |
E199556
|
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: Aricia | Statement: [Latin League, hasMember, Aricia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aricia Context triple: [Latin League, hasMember, Aricia]
-
A.
Aricia
chosen
Aricia was an ancient town in the Alban Hills of Latium, historically significant as a cult center of Diana and a key stop on the Via Appia near Rome.
-
B.
Arona
Arona is a town in northern Italy on the shores of Lake Maggiore, known for its historic architecture and as the birthplace of Saint Charles Borromeo.
-
C.
Arona
Arona is a coastal tourist municipality in southern Tenerife, Spain, known for its popular beach resorts such as Los Cristianos and Playa de las Américas.
-
D.
Angarano
Angarano is an Italian-origin surname most notably associated with American actor Michael Angarano.
-
E.
Aleria
Aleria is an ancient coastal town on the eastern side of Corsica, France, known for its significant Roman archaeological site and historical importance.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d75772c8190b02aef02ea6788e1 |
completed | April 18, 2026, 10:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007daa9f7c8190a9540d9a7a6ca6fb |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.