Triple
T16870250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanna Holborn Gray |
E421148
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Hanna
Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
|
E1238411
|
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: Hanna | Statement: [Hanna Holborn Gray, givenName, Hanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanna Context triple: [Hanna Holborn Gray, givenName, Hanna]
-
A.
Hanna
Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
-
B.
Hanna
"Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
-
C.
Hanna
Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
-
D.
Till
Till is a character in Anzia Yezierska’s novel "Sapphira and the Slave Girl," contributing to the book’s exploration of race, power, and personal freedom in antebellum America.
-
E.
Jejuri
Jejuri is a temple town in Maharashtra, India, renowned for its hilltop Khandoba temple and vibrant religious festivals.
- 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: Hanna Triple: [Hanna Holborn Gray, givenName, Hanna]
Generated description
Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hanna Target entity description: Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
-
A.
Hanna
Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
-
B.
Hanna
"Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
-
C.
Hanna
Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
-
D.
Till
Till is a character in Anzia Yezierska’s novel "Sapphira and the Slave Girl," contributing to the book’s exploration of race, power, and personal freedom in antebellum America.
-
E.
Jejuri
Jejuri is a temple town in Maharashtra, India, renowned for its hilltop Khandoba temple and vibrant religious festivals.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b50b85c08190b35d1c45ee0e9675 |
completed | April 18, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2aeb9908190964a9403402186fb |
completed | May 10, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a00c3c25e9481908327bb6646212368 |
completed | May 10, 2026, 5:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c44e37b48190a62b315ddbbd4ec4 |
completed | May 10, 2026, 5:45 p.m. |
Created at: April 10, 2026, 5:29 a.m.