Triple
T32038801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papyrus R (British Museum 10499) |
E818165
|
entity |
| Predicate | typeOfWorkContained |
P19231
|
FINISHED |
| Object | courtly tale |
—
|
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: courtly tale | Statement: [Papyrus R (British Museum 10499), typeOfWorkContained, courtly tale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWorkContained Context triple: [Papyrus R (British Museum 10499), typeOfWorkContained, courtly tale]
-
A.
typeOfWork
Indicates the kind or category of work associated with or performed by an entity.
-
B.
designedTypeOfWork
Indicates that one entity is the type or category of work for which another entity was specifically designed.
-
C.
partOfWorkType
chosen
Indicates that something is a component, subtype, or specific category within a broader type of work.
-
D.
settingOfWork
Indicates the place, time, or environment in which a creative work’s narrative or events are situated.
-
E.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
- 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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00332eaa0c8190a69ea895576bb0ee |
completed | May 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_6a0032b2ea80819083b89ebb88165933 |
completed | May 10, 2026, 7:24 a.m. |
Created at: May 1, 2026, 12:19 a.m.