Triple
T365923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanese cuisine |
E7958
|
entity |
| Predicate | servesDish |
P12772
|
FINISHED |
| Object |
baba ghanoush
Baba ghanoush is a Middle Eastern dip made from roasted eggplant blended with tahini, lemon juice, garlic, and seasonings.
|
E46463
|
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: baba ghanoush | Statement: [Lebanese cuisine, servesDish, baba ghanoush]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: baba ghanoush Context triple: [Lebanese cuisine, servesDish, baba ghanoush]
-
A.
Khachapuri
Khachapuri is a classic Georgian cheese-filled bread, often boat-shaped and topped with egg and butter, considered one of the country’s most iconic national dishes.
-
B.
Khinkali
Khinkali is a popular Georgian dumpling typically filled with spiced meat and broth, known for its distinctive twisted top and eaten by hand.
-
C.
Bacon
Bacon is a common English surname historically associated with notable figures such as the philosopher and statesman Francis Bacon.
-
D.
Mincha
Mincha is the Jewish afternoon prayer service, recited daily and given special liturgical significance on fast days and festivals such as Yom Kippur.
-
E.
Barbel
Barbel is a feminine given name, commonly used as a diminutive or variant of names like Barbara in German-speaking regions.
- 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: baba ghanoush Triple: [Lebanese cuisine, servesDish, baba ghanoush]
Generated description
Baba ghanoush is a Middle Eastern dip made from roasted eggplant blended with tahini, lemon juice, garlic, and seasonings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: baba ghanoush Target entity description: Baba ghanoush is a Middle Eastern dip made from roasted eggplant blended with tahini, lemon juice, garlic, and seasonings.
-
A.
Khachapuri
Khachapuri is a classic Georgian cheese-filled bread, often boat-shaped and topped with egg and butter, considered one of the country’s most iconic national dishes.
-
B.
Khinkali
Khinkali is a popular Georgian dumpling typically filled with spiced meat and broth, known for its distinctive twisted top and eaten by hand.
-
C.
Bacon
Bacon is a common English surname historically associated with notable figures such as the philosopher and statesman Francis Bacon.
-
D.
Mincha
Mincha is the Jewish afternoon prayer service, recited daily and given special liturgical significance on fast days and festivals such as Yom Kippur.
-
E.
Barbel
Barbel is a feminine given name, commonly used as a diminutive or variant of names like Barbara in German-speaking regions.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ee29ede0819095279af95b53e350 |
completed | Feb. 28, 2026, 1:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e8668b848190b68d19819ac134df |
completed | March 1, 2026, 7:19 a.m. |
| NEDg | Description generation | batch_69a3ea5beecc8190b128db693db39e95 |
completed | March 1, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3eba438548190912d5a4a9c0e6528 |
completed | March 1, 2026, 7:32 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.