Triple
T19914979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | writing the novel "Watership Down" |
E478641
|
entity |
| Predicate | hasThemeInResult |
P76865
|
FINISHED |
| Object | leadership |
—
|
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: leadership | Statement: [writing the novel "Watership Down", hasThemeInResult, leadership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeInResult Context triple: [writing the novel "Watership Down", hasThemeInResult, leadership]
-
A.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
B.
containsThemeArea
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
-
C.
hasThemeInStory
chosen
Indicates that a particular theme is present or plays a significant role within a given story.
-
D.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
E.
usesThemeFrom
Indicates that one work incorporates, references, or is based on the thematic material of another work.
- 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.