Triple
T16066570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omer |
E389746
|
entity |
| Predicate | hasNotableBearerExample |
P458
|
FINISHED |
| Object |
Omer Adam
Omer Adam is a popular Israeli singer known for his blend of Mizrahi and pop music and numerous chart-topping hits.
|
E1193270
|
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: Omer Adam | Statement: [Omer, hasNotableBearerExample, Omer Adam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omer Adam Context triple: [Omer, hasNotableBearerExample, Omer Adam]
-
A.
Omer Lay
Omer Lay is the father of Kenneth Lay, the former Enron CEO central to one of the largest corporate fraud scandals in U.S. history.
-
B.
Amir Ohana
Amir Ohana is an Israeli politician and lawyer from the Likud party who has served in several senior government roles, including as a cabinet minister and Knesset member.
-
C.
Omar Ishrak
Omar Ishrak is a Bangladeshi-American business executive best known for leading Medtronic as its longtime CEO and later serving as chairman of the company.
-
D.
Omer
Omer is a given name and surname used in various cultures, often as a variant of Omar, with roots in Arabic and Hebrew traditions.
-
E.
Yom Saeed
Yom Saeed is an early Egyptian film notable for featuring the debut screen appearance of legendary actress Faten Hamama.
- 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: Omer Adam Triple: [Omer, hasNotableBearerExample, Omer Adam]
Generated description
Omer Adam is a popular Israeli singer known for his blend of Mizrahi and pop music and numerous chart-topping hits.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Omer Adam Target entity description: Omer Adam is a popular Israeli singer known for his blend of Mizrahi and pop music and numerous chart-topping hits.
-
A.
Omer Lay
Omer Lay is the father of Kenneth Lay, the former Enron CEO central to one of the largest corporate fraud scandals in U.S. history.
-
B.
Amir Ohana
Amir Ohana is an Israeli politician and lawyer from the Likud party who has served in several senior government roles, including as a cabinet minister and Knesset member.
-
C.
Omar Ishrak
Omar Ishrak is a Bangladeshi-American business executive best known for leading Medtronic as its longtime CEO and later serving as chairman of the company.
-
D.
Omer
Omer is a given name and surname used in various cultures, often as a variant of Omar, with roots in Arabic and Hebrew traditions.
-
E.
Yom Saeed
Yom Saeed is an early Egyptian film notable for featuring the debut screen appearance of legendary actress Faten Hamama.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837ca628819081dfc439fe322d58 |
completed | April 17, 2026, 12:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe480d59c8190962ac596a872b5e0 |
completed | May 10, 2026, 1:50 a.m. |
| NEDg | Description generation | batch_69ffe6ee34788190942ef1d3bb805f78 |
completed | May 10, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffe7d127848190bbd79a8b94a49f93 |
completed | May 10, 2026, 2:05 a.m. |
Created at: April 10, 2026, 4:57 a.m.