Triple
T9853984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan & Naomi |
E239538
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Stephen Johnson
Stephen Johnson is a book editor known for his work on the children's novel "Alan & Naomi."
|
E825068
|
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: Stephen Johnson | Statement: [Alan & Naomi, editor, Stephen Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Johnson Context triple: [Alan & Naomi, editor, Stephen Johnson]
-
A.
Phil Schiller
Phil Schiller is a longtime Apple executive who has played a key role in the company’s product marketing and major keynote presentations.
-
B.
John Stankey
John Stankey is an American business executive best known as the chief executive officer of AT&T.
-
C.
Robb Armstrong
Robb Armstrong is an American cartoonist best known as the creator of the long-running syndicated comic strip "JumpStart."
-
D.
Christian Stovitz
Christian Stovitz is a stylish, charming new student and love interest in the 1995 teen comedy film "Clueless," known for his retro fashion sense and eventual revelation as gay.
-
E.
Mitchell Baker
Mitchell Baker is an American business leader and open-source advocate best known as the longtime chair and former CEO of Mozilla, where she has guided the development of the Firefox web browser and the organization’s internet-for-good mission.
- 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: Stephen Johnson Triple: [Alan & Naomi, editor, Stephen Johnson]
Generated description
Stephen Johnson is a book editor known for his work on the children's novel "Alan & Naomi."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stephen Johnson Target entity description: Stephen Johnson is a book editor known for his work on the children's novel "Alan & Naomi."
-
A.
Phil Schiller
Phil Schiller is a longtime Apple executive who has played a key role in the company’s product marketing and major keynote presentations.
-
B.
John Stankey
John Stankey is an American business executive best known as the chief executive officer of AT&T.
-
C.
Robb Armstrong
Robb Armstrong is an American cartoonist best known as the creator of the long-running syndicated comic strip "JumpStart."
-
D.
Christian Stovitz
Christian Stovitz is a stylish, charming new student and love interest in the 1995 teen comedy film "Clueless," known for his retro fashion sense and eventual revelation as gay.
-
E.
Mitchell Baker
Mitchell Baker is an American business leader and open-source advocate best known as the longtime chair and former CEO of Mozilla, where she has guided the development of the Firefox web browser and the organization’s internet-for-good mission.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5f21a04819099f23ede55ec3417 |
completed | April 5, 2026, 3:24 a.m. |
| NEDg | Description generation | batch_69d1d7a6a87c81908dcd79c776bb19a1 |
completed | April 5, 2026, 3:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d82007088190ac372c67a6760e65 |
completed | April 5, 2026, 3:33 a.m. |
Created at: March 30, 2026, 8:34 p.m.