Triple
T37174609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkansas attorneys |
E921004
|
entity |
| Predicate | mayBeAdmittedBy |
P113731
|
FINISHED |
| Object | bar examination |
—
|
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: bar examination | Statement: [Arkansas attorneys, mayBeAdmittedBy, bar examination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeAdmittedBy Context triple: [Arkansas attorneys, mayBeAdmittedBy, bar examination]
-
A.
mayBeAdmitted
chosen
Indicates that an entity has the possibility or permission to be allowed entry or accepted into another entity or context.
-
B.
mayAdmit
Indicates that one entity has the permission or authority to allow another entity to enter, join, or be accepted into something.
-
C.
mayAlsoAdmit
Indicates that an entity has the option or authority to additionally allow or accept another entity, beyond any primary or default admission.
-
D.
admittedTo
Indicates that one entity has been formally accepted, enrolled, or granted entry into another entity, such as an institution, program, or facility.
-
E.
hasAdmission
Indicates that an entity possesses or is associated with a specific admission event, record, or status (such as being admitted to a place, program, or institution).
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:15 p.m.