Triple
T441268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Langland |
E10117
|
entity |
| Predicate | primaryThemeInWork |
P2366
|
FINISHED |
| Object | quest for true Christian life |
—
|
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: quest for true Christian life | Statement: [William Langland, primaryThemeInWork, quest for true Christian life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryThemeInWork Context triple: [William Langland, primaryThemeInWork, quest for true Christian life]
-
A.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
primaryTask
Indicates that an entity has a main or most important task, role, or function it is responsible for above all others.
-
C.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
D.
primaryMotif
chosen
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
E.
primaryProduct
Indicates that one entity is the main or most important product associated with, produced by, or offered by 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2af84881909635ebbbb3465b1b |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.