Triple
T20617675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Bring Men to Christ |
E506607
|
entity |
| Predicate | hasReprintEditions |
P35037
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [How to Bring Men to Christ, hasReprintEditions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReprintEditions Context triple: [How to Bring Men to Christ, hasReprintEditions, yes]
-
A.
hasDifferentEditions
chosen
Indicates that an entity exists in multiple distinct versions or editions that differ in some characteristics.
-
B.
hasSerializedEditions
Indicates that an entity has one or more serialized editions or installments derived from it.
-
C.
numberOfEditions
Indicates the total count of distinct editions associated with a given entity.
-
D.
laterEditions
Indicates that one entity is a subsequent or more recent edition of another entity.
-
E.
hasEditionIn
Indicates that one entity has a specific edition or version that exists or is available in another entity (such as a particular format, language, or location).
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aadd30b88190af3a05527ad5ac64 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.