Triple
T995624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaia Wise |
E21488
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wise
Wise is a surname shared by various notable individuals across fields such as entertainment, politics, and academia.
|
E118203
|
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: Wise | Statement: [Gaia Wise, familyName, Wise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wise Context triple: [Gaia Wise, familyName, Wise]
-
A.
the Wise
The Wise is the honorific epithet of Frederick III, Elector of Saxony, renowned for protecting Martin Luther and playing a key role in the early Reformation.
-
B.
Wisdom
Wisdom is a common English surname borne by various notable individuals, including the British comedian and actor Norman Wisdom.
-
C.
Wisemen
"Wisemen" is a song by British singer-songwriter James Blunt, featured on his debut studio album "Back to Bedlam."
-
D.
Lord of Wisdom
Lord of Wisdom is an epithet of the Hindu deity Ganesha, highlighting his role as the divine patron of intellect, learning, and discernment.
-
E.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
- 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: Wise Triple: [Gaia Wise, familyName, Wise]
Generated description
Wise is a surname shared by various notable individuals across fields such as entertainment, politics, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wise Target entity description: Wise is a surname shared by various notable individuals across fields such as entertainment, politics, and academia.
-
A.
the Wise
The Wise is the honorific epithet of Frederick III, Elector of Saxony, renowned for protecting Martin Luther and playing a key role in the early Reformation.
-
B.
Wisdom
Wisdom is a common English surname borne by various notable individuals, including the British comedian and actor Norman Wisdom.
-
C.
Wisemen
"Wisemen" is a song by British singer-songwriter James Blunt, featured on his debut studio album "Back to Bedlam."
-
D.
Lord of Wisdom
Lord of Wisdom is an epithet of the Hindu deity Ganesha, highlighting his role as the divine patron of intellect, learning, and discernment.
-
E.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4df6dcc819084a7c0a50637a2c2 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a18db488190bf7d604fe6a33b9e |
completed | March 7, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_69ac2ab3df188190a70c46b276b562fe |
completed | March 7, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac2b28e9dc8190bdf5642def2399c5 |
completed | March 7, 2026, 1:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.