Triple
T31933898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hárslevelű |
E815331
|
entity |
| Predicate | synonymInEnglish |
P3575
|
FINISHED |
| Object |
Linden Leaf
Linden Leaf is the English name for Hárslevelű, a Hungarian white grape variety known for producing aromatic, full-bodied wines often used in Tokaj.
|
E1984265
|
NE FINISHED |
How this triple was built (3 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: Linden Leaf | Statement: [Hárslevelű, synonymInEnglish, Linden Leaf]
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: Linden Leaf Triple: [Hárslevelű, synonymInEnglish, Linden Leaf]
Generated description
Linden Leaf is the English name for Hárslevelű, a Hungarian white grape variety known for producing aromatic, full-bodied wines often used in Tokaj.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: synonymInEnglish Context triple: [Hárslevelű, synonymInEnglish, Linden Leaf]
-
A.
synonym
chosen
Indicates that two terms have the same or nearly the same meaning in a given context.
-
B.
meaningInLanguage
Indicates that an expression or symbol has a particular meaning or interpretation within a specified language.
-
C.
meaningInFinnish
Indicates that one entity expresses the meaning or translation of another entity in the Finnish language.
-
D.
meaningInGerman
Indicates that one entity expresses the meaning or translation of another entity in the German language.
-
E.
languageOfWord
Indicates that a particular language is the one in which a given word is expressed or defined.
- F. None of above.
Provenance (6 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b239024c81909c3b411b0bff1cbc |
completed | May 3, 2026, 2:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2e8a3f56a08190b5fe26e362aa0d03 |
completed | June 14, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_6a2e8af44d208190a478474dbd7d0178 |
completed | June 14, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2e8bea3a60819088295cb1c20f0f69 |
completed | June 14, 2026, 11:09 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:04 a.m.