Triple
T18576557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benenson |
E454001
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Joel Benenson
Joel Benenson is an American pollster and political strategist best known as the chief pollster for Barack Obama’s presidential campaigns.
|
E1332170
|
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: Joel Benenson | Statement: [Benenson, hasNotableBearer, Joel Benenson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joel Benenson Context triple: [Benenson, hasNotableBearer, Joel Benenson]
-
A.
Joel Berez
Joel Berez is an American businessman best known as a co-founder and early leader of the pioneering interactive fiction game company Infocom.
-
B.
Joel Engel
Joel Engel is a notable individual recognized for achievements significant enough to distinguish him among others sharing the surname Engel.
-
C.
Joel Benjamin
Joel Benjamin is an American chess grandmaster and author who notably served as a consultant for IBM's Deep Blue computer in its historic matches against Garry Kasparov.
-
D.
Joel Bergman
Joel Bergman was an American architect best known for designing iconic, large-scale casino resorts in Las Vegas.
-
E.
Joel Stillerman
Joel Stillerman is a television and film executive and producer known for his influential programming roles at networks like AMC and Hulu.
- 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: Joel Benenson Triple: [Benenson, hasNotableBearer, Joel Benenson]
Generated description
Joel Benenson is an American pollster and political strategist best known as the chief pollster for Barack Obama’s presidential campaigns.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joel Benenson Target entity description: Joel Benenson is an American pollster and political strategist best known as the chief pollster for Barack Obama’s presidential campaigns.
-
A.
Joel Berez
Joel Berez is an American businessman best known as a co-founder and early leader of the pioneering interactive fiction game company Infocom.
-
B.
Joel Engel
Joel Engel is a notable individual recognized for achievements significant enough to distinguish him among others sharing the surname Engel.
-
C.
Joel Benjamin
Joel Benjamin is an American chess grandmaster and author who notably served as a consultant for IBM's Deep Blue computer in its historic matches against Garry Kasparov.
-
D.
Joel Bergman
Joel Bergman was an American architect best known for designing iconic, large-scale casino resorts in Las Vegas.
-
E.
Joel Stillerman
Joel Stillerman is a television and film executive and producer known for his influential programming roles at networks like AMC and Hulu.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543cc94f081909b76c3d488ed5637 |
completed | April 19, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a04f88ad578819086a5dd6cc8b01f15 |
completed | May 13, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_6a04f9bcca8881908952767c4fc418c8 |
completed | May 13, 2026, 10:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04fa25d5d08190b28dae1a1ebb1ff6 |
completed | May 13, 2026, 10:24 p.m. |
Created at: April 10, 2026, 11:43 a.m.