Triple
T2157732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gutenberg Bible copies |
E47929
|
entity |
| Predicate | haveApproximateSurvivingCount |
P20367
|
FINISHED |
| Object | about 49 copies |
—
|
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: about 49 copies | Statement: [Gutenberg Bible copies, haveApproximateSurvivingCount, about 49 copies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveApproximateSurvivingCount Context triple: [Gutenberg Bible copies, haveApproximateSurvivingCount, about 49 copies]
-
A.
hasApproximateMemberCount
chosen
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
B.
hasSurvivorTerm
Indicates that an entity is associated with a term or label specifically used to describe survivors of an event, condition, or circumstance.
-
C.
killedApproximate
Indicates that one entity caused the death of another, but the information about this killing is uncertain, estimated, or not known with exact precision.
-
D.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
E.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe68fe0c8190beb5db003738a6e5 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.