Triple
T29109293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attilio Regolo |
E736849
|
entity |
| Predicate | firstPerformanceAsOpera |
P4982
|
FINISHED |
| Object |
Attilio Regolo (Hasse) 1750
Attilio Regolo (Hasse) 1750 is an opera seria by Johann Adolph Hasse, based on the story of the Roman consul Marcus Atilius Regulus and premiered in the mid-18th century.
|
E1849554
|
NE FINISHED |
How this triple was built (3 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: Attilio Regolo (Hasse) 1750 | Statement: [Attilio Regolo, firstPerformanceAsOpera, Attilio Regolo (Hasse) 1750]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Attilio Regolo (Hasse) 1750 Triple: [Attilio Regolo, firstPerformanceAsOpera, Attilio Regolo (Hasse) 1750]
Generated description
Attilio Regolo (Hasse) 1750 is an opera seria by Johann Adolph Hasse, based on the story of the Roman consul Marcus Atilius Regulus and premiered in the mid-18th century.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPerformanceAsOpera Context triple: [Attilio Regolo, firstPerformanceAsOpera, Attilio Regolo (Hasse) 1750]
-
A.
firstPerformanceInOpera
Indicates that an entity’s first-ever performance occurred in the context of an opera production.
-
B.
firstPerformanceOpera
Indicates the relationship in which an opera work is presented in its first-ever performance.
-
C.
firstPerformanceTheatreWithOpera
Indicates that a theatre hosted its first performance that included an opera.
-
D.
firstPerformance
chosen
Indicates that an entity marks the initial or debut performance of another entity, such as a work, artist, or production.
-
E.
firstPerformanceOperaYear
Indicates the year in which an opera was first performed.
- F. None of above.
Provenance (6 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a008e29f76881908e656dbbd7fceea3 |
completed | May 10, 2026, 1:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2537c079688190b8142efa06575188 |
completed | June 7, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_6a253bde7d1c819082d2aeac0b835460 |
completed | June 7, 2026, 9:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a253fc091b8819091f9253f88e27df4 |
completed | June 7, 2026, 9:54 a.m. |
| PD | Predicate disambiguation | batch_6a008dc01b308190bc26e69814692f82 |
completed | May 10, 2026, 1:53 p.m. |
Created at: April 28, 2026, 11:17 a.m.