Triple
T32832211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | From the Diary of Anne Frank |
E839720
|
entity |
| Predicate | usesTextExcerptsFrom |
P64118
|
FINISHED |
| Object | Anne Frank |
—
|
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: Anne Frank | Statement: [From the Diary of Anne Frank, usesTextExcerptsFrom, Anne Frank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTextExcerptsFrom Context triple: [From the Diary of Anne Frank, usesTextExcerptsFrom, Anne Frank]
-
A.
usesTextBy
Indicates that one entity makes use of or relies on a text authored or provided by another entity.
-
B.
textsIncludedIn
Indicates that certain texts are contained within, or form a subset of, a larger collection or body of texts.
-
C.
hasExcerpt
chosen
Indicates that one entity contains or is associated with a selected portion or extract taken from another entity.
-
D.
basedOnText
Indicates that something is derived, adapted, or developed from a specific text source.
-
E.
followsInText
Indicates that one textual element appears immediately or subsequently after another within the same text.
- 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_69f3493f22f88190ae6dd4bc15b6cf8d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 1, 2026, 1:16 a.m.