Triple
T3167753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Engadget |
E66252
|
entity |
| Predicate | notableEditor |
P1932
|
FINISHED |
| Object |
Dana Wollman
Dana Wollman is a technology journalist and editor best known for her leadership and editorial work at the consumer tech news site Engadget.
|
E351209
|
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: Dana Wollman | Statement: [Engadget, notableEditor, Dana Wollman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Wollman Context triple: [Engadget, notableEditor, Dana Wollman]
-
A.
Dana Glauberman
Dana Glauberman is an American film editor known for her work on numerous high-profile feature films and collaborations with director Jason Reitman.
-
B.
Wendy Finerman
Wendy Finerman is an American film producer best known for her work on hit movies such as "Forrest Gump" and "The Devil Wears Prada."
-
C.
Kate Wollman
Kate Wollman was a philanthropist whose donation funded the construction of the famous Wollman Rink in New York City's Central Park.
-
D.
Deborah Waxman
Deborah Waxman is an American rabbi and scholar who serves as a leading contemporary voice and institutional leader within Reconstructionist Judaism.
-
E.
Bonnie Perlman
Bonnie Perlman is an actress known for appearing in the television series "Obsessed."
- 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: Dana Wollman Triple: [Engadget, notableEditor, Dana Wollman]
Generated description
Dana Wollman is a technology journalist and editor best known for her leadership and editorial work at the consumer tech news site Engadget.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dana Wollman Target entity description: Dana Wollman is a technology journalist and editor best known for her leadership and editorial work at the consumer tech news site Engadget.
-
A.
Dana Glauberman
Dana Glauberman is an American film editor known for her work on numerous high-profile feature films and collaborations with director Jason Reitman.
-
B.
Wendy Finerman
Wendy Finerman is an American film producer best known for her work on hit movies such as "Forrest Gump" and "The Devil Wears Prada."
-
C.
Kate Wollman
Kate Wollman was a philanthropist whose donation funded the construction of the famous Wollman Rink in New York City's Central Park.
-
D.
Deborah Waxman
Deborah Waxman is an American rabbi and scholar who serves as a leading contemporary voice and institutional leader within Reconstructionist Judaism.
-
E.
Bonnie Perlman
Bonnie Perlman is an actress known for appearing in the television series "Obsessed."
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6457acc8190b2b9acbd1cfcdb91 |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b324ea81f4819080e836dccf8254d0 |
completed | March 12, 2026, 8:41 p.m. |
| NEDg | Description generation | batch_69b326960de48190abe69b3c140f4a4a |
completed | March 12, 2026, 8:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b327b13c9c8190b8c431ca2ae61ef9 |
completed | March 12, 2026, 8:53 p.m. |
Created at: March 8, 2026, 3:06 p.m.