Triple
T13892993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Material Girl |
E334019
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Peter Brown
Peter Brown is an American songwriter best known for co-writing Madonna’s hit song "Material Girl."
|
E1067578
|
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: Peter Brown | Statement: [Material Girl, writer, Peter Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Brown Context triple: [Material Girl, writer, Peter Brown]
-
A.
Peter Brown
Peter Brown was an American actor best known for his roles in 1950s–1960s television Westerns such as "Lawman" and "Laredo."
-
B.
Peter Browne
Peter Browne is a relatively common personal name shared by multiple notable individuals across fields such as politics, religion, and academia.
-
C.
Peter Harvey
Peter Harvey is a set designer known for his work on the production "Diamonds."
-
D.
Edward Hall
Edward Hall was a 16th-century English lawyer, historian, and chronicler best known for his influential Tudor-era chronicle "The Union of the Two Noble and Illustre Families of Lancastre and Yorke."
-
E.
John Guy
John Guy is a British historian and biographer best known for his acclaimed works on Tudor history, including a major biography of Mary, Queen of Scots.
- 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: Peter Brown Triple: [Material Girl, writer, Peter Brown]
Generated description
Peter Brown is an American songwriter best known for co-writing Madonna’s hit song "Material Girl."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Brown Target entity description: Peter Brown is an American songwriter best known for co-writing Madonna’s hit song "Material Girl."
-
A.
Peter Brown
Peter Brown was an American actor best known for his roles in 1950s–1960s television Westerns such as "Lawman" and "Laredo."
-
B.
Peter Browne
Peter Browne is a relatively common personal name shared by multiple notable individuals across fields such as politics, religion, and academia.
-
C.
Peter Harvey
Peter Harvey is a set designer known for his work on the production "Diamonds."
-
D.
Edward Hall
Edward Hall was a 16th-century English lawyer, historian, and chronicler best known for his influential Tudor-era chronicle "The Union of the Two Noble and Illustre Families of Lancastre and Yorke."
-
E.
John Guy
John Guy is a British historian and biographer best known for his acclaimed works on Tudor history, including a major biography of Mary, Queen of Scots.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a537d4819093c2bae2a244816a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71ca8a881908ac02687fbfe62fb |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c7e1247481908073c1e282c3619f |
completed | May 3, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c8f2b5588190b6143d676eb648a0 |
completed | May 3, 2026, 10:15 p.m. |
Created at: April 9, 2026, 10:15 p.m.