Triple
T12208705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reuel |
E290899
|
entity |
| Predicate | hasRelationshipDiscussion |
P103800
|
FINISHED |
| Object | scholarly debate on identity with Jethro |
—
|
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: scholarly debate on identity with Jethro | Statement: [Reuel, hasRelationshipDiscussion, scholarly debate on identity with Jethro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipDiscussion Context triple: [Reuel, hasRelationshipDiscussion, scholarly debate on identity with Jethro]
-
A.
hasDiscussionSystem
Indicates that an entity is equipped with or supports a system for facilitating discussions or conversations.
-
B.
hasDiscussionPages
Indicates that an entity is associated with one or more pages where discussions or conversations about it take place.
-
C.
hasRelationships
Indicates that an entity is connected to one or more other entities through specified types of relationships.
-
D.
containsDiscussionOf
Indicates that one entity includes or features a discussion, treatment, or consideration of another entity as a topic or subject.
-
E.
discussedAs
Indicates that one entity is talked about, treated, or examined in terms of another entity, often as an example, case, or framing concept.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d920c3dc9881908c396a4ab34f4836 |
completed | April 10, 2026, 4:09 p.m. |
Created at: April 8, 2026, 9:51 p.m.