Triple
T10981711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucius Scribonius Libo |
E259521
|
entity |
| Predicate | cognomen |
P6662
|
FINISHED |
| Object | Libo |
E713494
|
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: Libo | Statement: [Lucius Scribonius Libo, cognomen, Libo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Libo Context triple: [Lucius Scribonius Libo, cognomen, Libo]
-
A.
Libo
chosen
Libo is an ancient Roman cognomen associated with members of the patrician Julii family.
-
B.
Lugana
Lugana is an Italian white wine appellation near Lake Garda, renowned for its fresh, mineral-driven wines primarily made from the Turbiana grape.
-
C.
Lubja
Lubja is a small village located within Viimsi Parish in northern Estonia, near the capital city of Tallinn.
-
D.
Liboi
Liboi is a small Kenyan border town in the arid northeast near Somalia, serving as a local trading and transit point.
-
E.
Lubero
Lubero is a town and administrative center located in the mountainous region of North Kivu in the eastern Democratic Republic of the Congo.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ea940c8190ab3e62e89244f954 |
completed | April 9, 2026, 9:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d7d57a6c8190bcde1d7267708b3a |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 8, 2026, 9:24 p.m.