Triple
T35419624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holly Kennedy |
E1023743
|
entity |
| Predicate | lettersPurpose |
P182947
|
FINISHED |
| Object | to help her move on with her life |
—
|
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: to help her move on with her life | Statement: [Holly Kennedy, lettersPurpose, to help her move on with her life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lettersPurpose Context triple: [Holly Kennedy, lettersPurpose, to help her move on with her life]
-
A.
letters
Indicates that one entity is composed of, represented by, or associated with specific alphabetic characters or written symbols.
-
B.
lettersContent
Indicates that one entity is the textual content contained within a letter or written correspondence represented by another entity.
-
C.
letter3
Indicates that one entity is the third letter (or character) of another entity, typically a string or word.
-
D.
entryPurpose
Indicates the reason or intended use for which an entity is being entered, accessed, or recorded in a given context.
-
E.
letterType
Indicates the specific category or kind of letter associated with or assigned to an entity.
- 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79588cf848190b078b1dfb65da937 |
completed | May 3, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:03 p.m.