Triple
T26323464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvana |
E662180
|
entity |
| Predicate | nameMeaningTheme |
P28204
|
FINISHED |
| Object | woodland or forest-related |
—
|
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: woodland or forest-related | Statement: [Sylvana, nameMeaningTheme, woodland or forest-related]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameMeaningTheme Context triple: [Sylvana, nameMeaningTheme, woodland or forest-related]
-
A.
nameTheme
Indicates that one entity serves as the thematic or subject-related name associated with another entity.
-
B.
currentNameMeaning
chosen
Indicates that the predicate expresses the meaning or significance of an entity’s current name.
-
C.
birthNameMeaning
Indicates the semantic meaning or significance associated with a person's birth name.
-
D.
codeNameMeaning
Indicates that one entity is the meaning, interpretation, or significance associated with another entity’s code name.
-
E.
nameMeaningCertainty
Indicates how certain or confident a source is about the correctness or validity of an entity’s name meaning.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60f2e1fb48190aad56ac9683a267e |
completed | May 2, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 10:29 p.m.