Triple
T16448166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamba Sophia Jindan Duleep Singh |
E399485
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Sophia
Sophia is the given name of Bamba Sophia Jindan Duleep Singh, a historical figure associated with the Sikh royal lineage.
|
E1214494
|
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: Sophia | Statement: [Bamba Sophia Jindan Duleep Singh, givenName, Sophia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sophia Context triple: [Bamba Sophia Jindan Duleep Singh, givenName, Sophia]
-
A.
Sophia
Sophia of the Palatinate was a 17th-century German princess and Electress of Hanover, best known as the mother of King George I of Great Britain and a key figure in the Protestant succession to the British throne.
-
B.
Sophia
Sophia is a philosophical and theological concept signifying divine wisdom, often personified and associated with the rational principle of the cosmos.
-
C.
Sophia
Sophia is a person whose given name is used in the full name Sophia Chew Nicklin Dallas.
-
D.
Sophia
Sophia is a small town located in Raleigh County in the southern part of West Virginia, United States.
-
E.
Sophia
Sophia is the young, unhappily married woman at the center of the historical romance and art-themed drama in "Tulip Fever."
- 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: Sophia Triple: [Bamba Sophia Jindan Duleep Singh, givenName, Sophia]
Generated description
Sophia is the given name of Bamba Sophia Jindan Duleep Singh, a historical figure associated with the Sikh royal lineage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sophia Target entity description: Sophia is the given name of Bamba Sophia Jindan Duleep Singh, a historical figure associated with the Sikh royal lineage.
-
A.
Sophia
Sophia is the given name of Archduchess Anna Maria Sophia of Austria, a member of the Habsburg royal family.
-
B.
Sophia
Sophia is a person whose given name is used in the full name Sophia Chew Nicklin Dallas.
-
C.
Sophia
Sophia is the given name of Queen Sofía of Spain, the former queen consort known for her long-standing role in the Spanish royal family and public life.
-
D.
Sophia
Sophia was a prominent Byzantine empress of the Justinian dynasty, known for her political influence and role in imperial court affairs during the 6th century.
-
E.
Sophia
Sophia is the birth name of American actress Sylvia Sidney, a prominent film and stage performer of the 1930s and later character roles.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cddfc3c8190919b49f74b7e8e1a |
completed | April 18, 2026, 7:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f4b738881908f8a205466397f33 |
completed | May 10, 2026, 9:26 a.m. |
| NEDg | Description generation | batch_6a0050751be48190a76ab998b544ac5a |
completed | May 10, 2026, 9:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0050d99f7c81909a5d5582294790f7 |
completed | May 10, 2026, 9:33 a.m. |
Created at: April 10, 2026, 5:10 a.m.