Triple
T31172003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pension Grillparzer (introduction) |
E794632
|
entity |
| Predicate | includedInSection |
P56991
|
FINISHED |
| Object | fiction section of Trying to Save Piggy Sneed |
—
|
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: fiction section of Trying to Save Piggy Sneed | Statement: [The Pension Grillparzer (introduction), includedInSection, fiction section of Trying to Save Piggy Sneed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedInSection Context triple: [The Pension Grillparzer (introduction), includedInSection, fiction section of Trying to Save Piggy Sneed]
-
A.
usesSectionOf
Indicates that one entity makes use of a specific section or part of another entity.
-
B.
includedBy
chosen
Indicates that one entity is contained within, encompassed by, or treated as a subset or member of another entity.
-
C.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
D.
operatorInSection
Indicates that an operator is assigned to, works within, or is responsible for a specific section.
-
E.
includedInDocument
Indicates that one entity is contained or referenced within a particular document.
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00d08e8fac8190b59359134e6e1c03 |
completed | May 10, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_6a00d0127c088190a6f5b360450af113 |
completed | May 10, 2026, 6:36 p.m. |
Created at: April 29, 2026, 9:07 p.m.