Triple
T24785362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnes Nutter |
E620101
|
entity |
| Predicate | bookCharacteristic |
P157125
|
FINISHED |
| Object | complete and accurate to the end of the world |
—
|
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: complete and accurate to the end of the world | Statement: [Agnes Nutter, bookCharacteristic, complete and accurate to the end of the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookCharacteristic Context triple: [Agnes Nutter, bookCharacteristic, complete and accurate to the end of the world]
-
A.
seriesCharacteristic
Indicates that something is a defining feature, attribute, or property associated with a particular series.
-
B.
book
Indicates that an agent reserves or schedules a service, event, or resource for future use.
-
C.
noteCharacteristic
Indicates that one entity records, marks, or specifies a particular characteristic or attribute of another entity.
-
D.
bookCategory
Indicates the classification or genre category to which a given book belongs.
-
E.
termCharacteristics
Indicates the defining properties, attributes, or features that characterize a given term.
- F. None of above. chosen
Provenance (4 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_69e2fabdbe8c8190adbb9434b8636cad |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410a001788190a457e41f53aaf90c |
completed | May 1, 2026, 2:32 a.m. |
Created at: April 18, 2026, 4:45 a.m.