Triple
T19872432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 洛河 |
E477550
|
entity |
| Predicate | 在文学中的形象 |
P27711
|
FINISHED |
| Object | 多被描写为柔美清澈的河流 |
—
|
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: 多被描写为柔美清澈的河流 | Statement: [洛河, 在文学中的形象, 多被描写为柔美清澈的河流]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 在文学中的形象 Context triple: [洛河, 在文学中的形象, 多被描写为柔美清澈的河流]
-
A.
functionInLiterature
Indicates that one entity serves a particular narrative, rhetorical, or thematic role within a literary work in relation to another entity.
-
B.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
inLiterature
chosen
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
E.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d826f88190be04188997952d1b |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.