Triple
T2625941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letitia James |
E59116
|
entity |
| Predicate | hasProfessionalLicense |
P12714
|
FINISHED |
| Object | license to practice law in New York |
—
|
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: license to practice law in New York | Statement: [Letitia James, hasProfessionalLicense, license to practice law in New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalLicense Context triple: [Letitia James, hasProfessionalLicense, license to practice law in New York]
-
A.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
hasLicense
chosen
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
C.
hasProfessionalStatusRequirement
Indicates that something is subject to a condition specifying a particular professional status that must be held or met.
-
D.
isPro
Indicates that an entity is a professional or expert in a particular field, activity, or domain.
-
E.
supportsLicense
Indicates that one entity is compatible with, enables, or is configured to work under a specified license.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.