Triple
T24769087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transylvania |
E619669
|
entity |
| Predicate | literalGloss |
P128854
|
FINISHED |
| Object | on the other side of the forest |
—
|
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: on the other side of the forest | Statement: [Transylvania, literalGloss, on the other side of the forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literalGloss Context triple: [Transylvania, literalGloss, on the other side of the forest]
-
A.
meaningGloss
chosen
Indicates that the predicate provides a brief explanatory phrase or paraphrase capturing the meaning or sense of another expression or item.
-
B.
literalMeaningApproximation
Indicates that one entity expresses an approximate or rough literal meaning of another entity, rather than an exact or fully precise interpretation.
-
C.
figurativeMeaning
Indicates that one entity is used in a non-literal, metaphorical, or symbolic sense to convey a meaning about another entity or concept.
-
D.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
E.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 4:29 a.m.