Triple
T10344591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Asner |
E243711
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Asner
Asner is the surname of American actor and activist Ed Asner, best known for his role as Lou Grant on "The Mary Tyler Moore Show" and its spin-off.
|
E858429
|
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: Asner | Statement: [Ed Asner, familyName, Asner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asner Context triple: [Ed Asner, familyName, Asner]
-
A.
Ottis
Ottis is a masculine given name most notably borne by former NFL running back Ottis Anderson.
-
B.
Irwin
Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
-
C.
O'Steen
O'Steen is a surname most notably associated with American film editor Sam O'Steen, known for his work on several acclaimed Hollywood films.
-
D.
Irvin
Irvin is a surname most prominently associated with former NFL wide receiver and sports commentator Michael Irvin.
-
E.
Ainley
Ainley is an English surname most notably associated with actor Anthony Ainley, known for his role as the Master in the classic Doctor Who series.
- 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: Asner Triple: [Ed Asner, familyName, Asner]
Generated description
Asner is the surname of American actor and activist Ed Asner, best known for his role as Lou Grant on "The Mary Tyler Moore Show" and its spin-off.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asner Target entity description: Asner is the surname of American actor and activist Ed Asner, best known for his role as Lou Grant on "The Mary Tyler Moore Show" and its spin-off.
-
A.
Ottis
Ottis is a masculine given name most notably borne by former NFL running back Ottis Anderson.
-
B.
Irwin
Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
-
C.
O'Steen
O'Steen is a surname most notably associated with American film editor Sam O'Steen, known for his work on several acclaimed Hollywood films.
-
D.
Marlo
Marlo is a fictional character associated with Tully, likely appearing in a narrative centered on that figure.
-
E.
Irvin
Irvin is a surname most prominently associated with former NFL wide receiver and sports commentator Michael Irvin.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9228cd88190bcd94b85537233c1 |
completed | April 7, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d75077dfbc81908de29aac1a3bb19f |
completed | April 9, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69d7618c9abc819080c4d6669dfb8320 |
completed | April 9, 2026, 8:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7702ae24481908b0f5319413e81d4 |
completed | April 9, 2026, 9:23 a.m. |
Created at: April 6, 2026, 11:55 a.m.