Triple
T23340979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlioz’s Les Troyens à Carthage |
E591732
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Narbal |
—
|
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: Narbal | Statement: [Berlioz’s Les Troyens à Carthage, featuresCharacter, Narbal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narbal Context triple: [Berlioz’s Les Troyens à Carthage, featuresCharacter, Narbal]
-
A.
Narbal
chosen
Narbal is a Phoenician nobleman and advisor to Queen Dido in Hector Berlioz’s opera *Les Troyens*.
-
B.
Belbari
Belbari is a growing municipality and commercial center in eastern Nepal’s Koshi Province, known for its agricultural surroundings and role as a local hub within Morang District.
-
C.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
D.
Arganil
Arganil is a municipality and town in central Portugal known for its mountainous landscapes, river beaches, and traditional schist villages.
-
E.
Nabas
Nabas is a coastal municipality in the province of Aklan in the Philippines, known for its beaches, wind farms, and proximity to the resort island of Boracay.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198329d9c8190992627afa9b54bed |
completed | April 29, 2026, 5:33 a.m. |
Created at: April 17, 2026, 5:18 p.m.