Triple
T5598709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl Baldwin of Bewdley |
E147060
|
entity |
| Predicate | firstHolderOccupation |
P4891
|
FINISHED |
| Object | Prime Minister of the United Kingdom |
—
|
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: Prime Minister of the United Kingdom | Statement: [Earl Baldwin of Bewdley, firstHolderOccupation, Prime Minister of the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstHolderOccupation Context triple: [Earl Baldwin of Bewdley, firstHolderOccupation, Prime Minister of the United Kingdom]
-
A.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
B.
firstOfficeHolder
chosen
Indicates that the subject is the very first individual to hold a particular office or position associated with the object.
-
C.
recipientOccupation
Indicates that the object specifies the job, profession, or role held by the recipient in the described relationship or event.
-
D.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
E.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020d82870819087f9591b5a1021ce |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1890ec8190b9e6fa488792e4d4 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.