Triple
T34586396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Purchase African M.E. Church |
E888054
|
entity |
| Predicate | chapterAppearance |
P179350
|
FINISHED |
| Object | appears in early middle chapters of To Kill a Mockingbird |
—
|
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: appears in early middle chapters of To Kill a Mockingbird | Statement: [First Purchase African M.E. Church, chapterAppearance, appears in early middle chapters of To Kill a Mockingbird]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chapterAppearance Context triple: [First Purchase African M.E. Church, chapterAppearance, appears in early middle chapters of To Kill a Mockingbird]
-
A.
chapterMentioned
Indicates that a specific chapter is referenced or cited within a given context or source.
-
B.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
C.
partOfBook
Indicates that one entity is a component or section contained within a larger book entity.
-
D.
seatOfChapter
Indicates that a location serves as the official meeting place or headquarters for a specific chapter (such as a local branch of an organization).
-
E.
chapterAfter
Indicates that one chapter directly follows another in a sequential ordering.
- 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_69f349d25cbc8190869998de5915886b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720c8e74c819084f402fb9f935513 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71f8df5d48190944fbfbd9d573868 |
completed | May 3, 2026, 10:12 a.m. |
Created at: May 1, 2026, 2:03 a.m.