Triple
T3249617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Local color writing |
E68143
|
entity |
| Predicate | analyzedWithConcept |
P30899
|
FINISHED |
| Object | place and space in literature |
—
|
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: place and space in literature | Statement: [Local color writing, analyzedWithConcept, place and space in literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analyzedWithConcept Context triple: [Local color writing, analyzedWithConcept, place and space in literature]
-
A.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
C.
helpsAnalyze
chosen
Indicates that one entity assists another in examining, interpreting, or understanding something in a more detailed or effective way.
-
D.
partOfConcept
Indicates that one concept is a constituent or component of a larger, more encompassing concept.
-
E.
unitOfAnalysis
Indicates the primary entity, level, or component that is being examined or measured in a given analysis or study.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.