Triple
T36410878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shakespearean histories |
E896875
|
entity |
| Predicate | canonicalSubset |
P34732
|
FINISHED |
| Object | First tetralogy |
—
|
NE NERFINISHED |
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: First tetralogy | Statement: [Shakespearean histories, canonicalSubset, First tetralogy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonicalSubset Context triple: [Shakespearean histories, canonicalSubset, First tetralogy]
-
A.
coreSubset
Indicates that one set forms the essential or most important subset of another set, capturing its core elements.
-
B.
canonicalSetIncludes
chosen
Indicates that a canonical or standard set contains the referenced element as one of its members.
-
C.
subset
Indicates that all elements of one set are contained within another set.
-
D.
notEverySubsetIs
Indicates that it is not the case that every subset of one set satisfies a specified relation or property with respect to another set.
-
E.
canonicalFor
Indicates that one entity serves as the authoritative or standard representation for another, often consolidating or standing in for its variants or duplicates.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.