Triple
T21081921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Carthage |
E519390
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | Aeneid |
—
|
NE NERFINISHED |
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: Aeneid | Statement: [Queen of Carthage, appearsIn, Aeneid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aeneid Context triple: [Queen of Carthage, appearsIn, Aeneid]
-
A.
Virgil's Aeneid
chosen
Virgil's Aeneid is a Latin epic poem that narrates the legendary journey of Aeneas from the ruins of Troy to Italy, laying a mythic foundation for the origins of Rome.
-
B.
Les Troyens
Les Troyens is a grand five-act French opera by Hector Berlioz, inspired by Virgil’s Aeneid and renowned for its epic scale and rich orchestration.
-
C.
Enneüs
Enneüs is a Dutch given name most notably borne by politician Enneüs Heerma.
-
D.
Troy and the Trojans
"Troy and the Trojans" is an influential archaeological and historical study of ancient Troy and its inhabitants, authored by American archaeologist Carl Blegen.
-
E.
Aeneas at Delos
"Aeneas at Delos" is a 17th-century landscape painting by Claude Lorrain that depicts the mythological hero Aeneas visiting the sacred island of Delos within a luminous, idealized classical seaport setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702db430c81908a1547d8fbe45506 |
completed | April 21, 2026, 4:53 a.m. |
Created at: April 16, 2026, 2:49 p.m.