Triple
T38108465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Physician's Tale |
E951585
|
entity |
| Predicate | positionInCanterburyTales |
P37669
|
FINISHED |
| Object | one of the later tales in the fragmentary order |
—
|
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: one of the later tales in the fragmentary order | Statement: [The Physician's Tale, positionInCanterburyTales, one of the later tales in the fragmentary order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInCanterburyTales Context triple: [The Physician's Tale, positionInCanterburyTales, one of the later tales in the fragmentary order]
-
A.
positionInFiction
Indicates that one entity holds a specific role, status, or placement within a fictional work or narrative.
-
B.
narrativeLocationRelativeToCamelot
Indicates the spatial or contextual position of a narrative’s events relative to Camelot.
-
C.
positionInStory
chosen
Indicates the point or role an event, character, or element occupies within the overall sequence or structure of a story.
-
D.
positionInAuthorOeuvre
Indicates the relative placement or order of a work within an author's overall body of work.
-
E.
titleCharacterLocation
Indicates the location or setting associated with the main character referenced in the title.
- 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_69f76f065ed08190bdfb1b6d817f5b39 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0010e46d948190a51111b5270fade7 |
completed | May 10, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_6a001061d34c8190bfe73f3d7c061eb7 |
completed | May 10, 2026, 4:58 a.m. |
Created at: May 3, 2026, 4:21 p.m.