Triple
T2244320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pampa |
E49466
|
entity |
| Predicate | literaryFormUsed |
P6480
|
FINISHED |
| Object | kanda metre |
—
|
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: kanda metre | Statement: [Pampa, literaryFormUsed, kanda metre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryFormUsed Context triple: [Pampa, literaryFormUsed, kanda metre]
-
A.
hasLiteraryForm
chosen
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
B.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
E.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0e8d5648190915ff689c7ca42bc |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.