Triple
T190137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul |
E3700
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object |
Paula
Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
|
E40562
|
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: Paula | Statement: [Paul, hasFeminineForm, Paula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paula Context triple: [Paul, hasFeminineForm, Paula]
-
A.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
B.
Sara
Sara is a feminine given name of Hebrew origin meaning "princess," historically borne by notable figures including Sara Ann Delano Roosevelt, the mother of U.S. President Franklin D. Roosevelt.
-
C.
Claudia
Claudia is a feminine given name used in various cultures, derived from the ancient Roman family name Claudius.
-
D.
Rebeca
Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
-
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: Paula Triple: [Paul, hasFeminineForm, Paula]
Generated description
Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paula Target entity description: Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
-
A.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
B.
Sara
Sara is a feminine given name of Hebrew origin meaning "princess," historically borne by notable figures including Sara Ann Delano Roosevelt, the mother of U.S. President Franklin D. Roosevelt.
-
C.
Claudia
Claudia is a feminine given name used in various cultures, derived from the ancient Roman family name Claudius.
-
D.
Rebeca
Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
-
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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594c385481909e1e088e45c460a4 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c41191a08190afc0fd06d6845d68 |
completed | March 1, 2026, 4:44 a.m. |
| NEDg | Description generation | batch_69a3c562ebb88190a01b4621cf4512aa |
completed | March 1, 2026, 4:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3c5b8a64c8190a8526e70c49554dd |
completed | March 1, 2026, 4:51 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.