Triple
T245933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Project Ozma |
E5036
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Princess Ozma
Princess Ozma is a fictional royal character from L. Frank Baum’s Oz book series, serving as the rightful ruler of the Land of Oz.
|
E31704
|
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: Princess Ozma | Statement: [Project Ozma, namedAfter, Princess Ozma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Princess Ozma Context triple: [Project Ozma, namedAfter, Princess Ozma]
-
A.
Princess May
Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
-
B.
Princess Kiko
Princess Kiko is a member of Japan’s imperial family, known as the wife of Crown Prince Fumihito and mother of Prince Hisahito, the only male heir of his generation.
-
C.
Hilda
Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
-
D.
Maia
Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
-
E.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
- 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: Princess Ozma Triple: [Project Ozma, namedAfter, Princess Ozma]
Generated description
Princess Ozma is a fictional royal character from L. Frank Baum’s Oz book series, serving as the rightful ruler of the Land of Oz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Princess Ozma Target entity description: Princess Ozma is a fictional royal character from L. Frank Baum’s Oz book series, serving as the rightful ruler of the Land of Oz.
-
A.
Princess May
Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
-
B.
Princess Kiko
Princess Kiko is a member of Japan’s imperial family, known as the wife of Crown Prince Fumihito and mother of Prince Hisahito, the only male heir of his generation.
-
C.
Hilda
Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
-
D.
Maia
Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
-
E.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d128c0081909908825b302ae635 |
completed | Feb. 28, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36cf4d8608190bf3d33ee6b93aae0 |
completed | Feb. 28, 2026, 10:32 p.m. |
| NEDg | Description generation | batch_69a36d7b01fc8190a5c596b748bbaa53 |
completed | Feb. 28, 2026, 10:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a36df1839081909c743e1357dd400a |
completed | Feb. 28, 2026, 10:36 p.m. |
Created at: Feb. 28, 2026, 2:54 a.m.