Triple
T19914973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | writing the novel "Watership Down" |
E478641
|
entity |
| Predicate | hasPrimarySettingOfResult |
P131520
|
FINISHED |
| Object | rural England |
—
|
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: rural England | Statement: [writing the novel "Watership Down", hasPrimarySettingOfResult, rural England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySettingOfResult Context triple: [writing the novel "Watership Down", hasPrimarySettingOfResult, rural England]
-
A.
hasMainResult
Indicates that one entity is the primary or most significant outcome, conclusion, or result produced by another entity or process.
-
B.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
C.
hasPrimaryLocationSetting
chosen
Indicates that an entity is associated with its main or default geographic or contextual location.
-
D.
hasPrimaryFeature
Indicates that an entity possesses a main or most characteristic feature that defines or distinguishes it.
-
E.
hasPrimarySee
Indicates that one entity is designated as the main or preferred "see" reference or cross-reference for another 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6599394f081909246006c2e83bacc |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.