Triple
T26572017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Alabama ex rel. John Patterson, Attorney General |
E666851
|
entity |
| Predicate | officeHeldByRelator |
P45587
|
FINISHED |
| Object | Attorney General of Alabama |
—
|
NE NERFINISHED |
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: Attorney General of Alabama | Statement: [State of Alabama ex rel. John Patterson, Attorney General, officeHeldByRelator, Attorney General of Alabama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldByRelator Context triple: [State of Alabama ex rel. John Patterson, Attorney General, officeHeldByRelator, Attorney General of Alabama]
-
A.
officeHeldByActor
Indicates that a specific office, position, or role is held or occupied by a particular actor.
-
B.
relatorGeneral
Indicates a general, non-specific relationship or association between entities that does not fall under a more specialized relation type.
-
C.
officeHeldByMember
Indicates that a specific office or position is held or occupied by a particular member.
-
D.
officeHeldOf
chosen
Indicates that a specific office or position is (or was) held by a particular person or entity.
-
E.
officeHeldByLeaderOf
Indicates that a specific office or position is occupied by the leader of a given entity.
- 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_69ee9cfa21c081909e4e36e087debfc6 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 27, 2026, 1:58 a.m.