Triple
T9256017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Propertius |
E222444
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Monobiblos |
E651580
|
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: Monobiblos | Statement: [Propertius, notableWork, Monobiblos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monobiblos Context triple: [Propertius, notableWork, Monobiblos]
-
A.
Lezgin
Lezgin is a Northeast Caucasian language spoken primarily by the Lezgin people in southern Dagestan (Russia) and northern Azerbaijan.
-
B.
Codex
Codex is an AI system developed by OpenAI that translates natural language into code and powers tools like GitHub Copilot.
-
C.
Hexabiblos
chosen
Hexabiblos is a 14th-century Byzantine legal compendium compiled by Constantine Harmenopoulos that systematized and preserved Byzantine civil law for later use in the Greek world and beyond.
-
D.
Dua Libro
"Dua Libro" is the second major book in the early Esperanto literature corpus, continuing the development and promotion of the Esperanto language after "Unua Libro."
-
E.
Mens et Manus
Mens et Manus is the Latin motto of the Massachusetts Institute of Technology, expressing the union of mind and hand in the pursuit of knowledge and practical application.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b4e2048190af0d65b904677c36 |
completed | April 1, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09bde36688190bf66669f585dcee7 |
completed | April 4, 2026, 5:04 a.m. |
Created at: March 30, 2026, 7:32 p.m.