Triple
T7440857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiaramonti |
E171746
|
entity |
| Predicate | hasMemberWhoBecame |
P76419
|
FINISHED |
| Object | pope |
—
|
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: pope | Statement: [Chiaramonti, hasMemberWhoBecame, pope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberWhoBecame Context triple: [Chiaramonti, hasMemberWhoBecame, pope]
-
A.
hadMember
Indicates that an entity was formerly a member or part of another entity or group.
-
B.
memberBecame
Indicates that an entity transitioned into becoming a member of a group, organization, or collection at a specific point in time.
-
C.
hadNumberOfMembers
Indicates that an entity possessed or was associated with a specific count of members at a given time or in a given context.
-
D.
hasMemberFrom
Indicates that a group, organization, or collection includes at least one member originating from or belonging to a specified source, place, or category.
-
E.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34d84008190936af2b3670ef210 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:13 p.m.