Triple
T19485904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirga Gražinytė-Tyla |
E487510
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mirga
Mirga is a Lithuanian conductor best known for her tenure as music director of the City of Birmingham Symphony Orchestra.
|
E1378545
|
NE FINISHED |
How this triple was built (4 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: Mirga | Statement: [Mirga Gražinytė-Tyla, givenName, Mirga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mirga Context triple: [Mirga Gražinytė-Tyla, givenName, Mirga]
-
A.
Mangaya
Mangaya is an exonym referring to the Mandaya, an indigenous ethnic group of Mindanao in the southern Philippines known for their rich weaving traditions and upland farming.
-
B.
Miasino
Miasino is a small Italian town in the Piedmont region, known for its scenic location near Lake Orta and its historic villas and churches.
-
C.
Musaga
Musaga is a small hamlet (frazione) of the lakeside town of Gargnano in the Lombardy region of northern Italy.
-
D.
Girga
Girga is an ancient town in Upper Egypt, historically significant as a regional center along the Nile.
-
E.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Mirga Triple: [Mirga Gražinytė-Tyla, givenName, Mirga]
Generated description
Mirga is a Lithuanian conductor best known for her tenure as music director of the City of Birmingham Symphony Orchestra.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mirga Target entity description: Mirga is a Lithuanian conductor best known for her tenure as music director of the City of Birmingham Symphony Orchestra.
-
A.
Mangaya
Mangaya is an exonym referring to the Mandaya, an indigenous ethnic group of Mindanao in the southern Philippines known for their rich weaving traditions and upland farming.
-
B.
Miasino
Miasino is a small Italian town in the Piedmont region, known for its scenic location near Lake Orta and its historic villas and churches.
-
C.
Musaga
Musaga is a small hamlet (frazione) of the lakeside town of Gargnano in the Lombardy region of northern Italy.
-
D.
Girga
Girga is an ancient town in Upper Egypt, historically significant as a regional center along the Nile.
-
E.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
- F. None of above. chosen
Provenance (5 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343f46e88190b7ba65c210285bee |
completed | April 20, 2026, 2:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a074059d9948190bb54e2df1713927b |
completed | May 15, 2026, 3:48 p.m. |
| NEDg | Description generation | batch_6a07411bd900819099237aaee874411b |
completed | May 15, 2026, 3:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a074197aa14819096a74aab7bca9e3c |
completed | May 15, 2026, 3:53 p.m. |
Created at: April 10, 2026, 1:39 p.m.