Triple
T4190669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count (continental Europe) |
E89025
|
entity |
| Predicate | traditionallyConferredBy |
P54568
|
FINISHED |
| Object | monarch |
—
|
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: monarch | Statement: [Count (continental Europe), traditionallyConferredBy, monarch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionallyConferredBy Context triple: [Count (continental Europe), traditionallyConferredBy, monarch]
-
A.
conferredIn
Indicates that something (such as a degree, title, or honor) was formally granted or awarded within a particular context, event, or institution.
-
B.
formerConferredBy
Indicates that an honor, title, or status was previously granted to an entity by a specific conferring agent or institution, but is no longer currently held.
-
C.
degreeGrantedBy
Indicates that a specific academic degree was officially conferred by a particular granting institution.
-
D.
conferredOn
Indicates that something (such as an honor, title, degree, or benefit) has been formally granted or bestowed upon a particular entity.
-
E.
grantsDegreesFrom
Indicates that an institution has the authority to confer academic degrees originating from a specified source or program.
- 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af04b009dc8190abda3f149a5b16fa |
completed | March 9, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69af01935064819096b7619f42e164dd |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af04af4e44819098a9d7f91e65adf2 |
completed | March 9, 2026, 5:34 p.m. |
Created at: March 9, 2026, 3:46 p.m.