Triple
T14429921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malaga (grape) |
E357795
|
entity |
| Predicate | synonymStatus |
P3575
|
FINISHED |
| Object | historical synonym |
—
|
LITERAL FINISHED |
How this triple was built (2 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: historical synonym | Statement: [Malaga (grape), synonymStatus, historical synonym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: synonymStatus Context triple: [Malaga (grape), synonymStatus, historical synonym]
-
A.
synonym
chosen
Indicates that two terms have the same or nearly the same meaning in a given context.
-
B.
lexiconStatus
Indicates the current state or condition of a lexical item within a lexicon, such as whether it is active, deprecated, provisional, or otherwise classified.
-
C.
meaningStatus
Indicates the relationship between an entity and the status of its meaning, such as whether its meaning is defined, clear, ambiguous, or unknown.
-
D.
hasGlossonym
Indicates a relationship where an entity is associated with the specific name or term used to refer to a language (its glossonym).
-
E.
exonymStatus
Indicates the status or classification of a name used in one language to refer to a place, people, or entity known by a different name in its own language.
- F. None of above.
Provenance (3 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91154de881909266ae88d1545685 |
completed | April 14, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.