Triple
T5013210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Jones |
E112675
|
entity |
| Predicate | legalStatusOfUse |
P2250
|
FINISHED |
| Object | illegal |
—
|
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: illegal | Statement: [John Jones, legalStatusOfUse, illegal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusOfUse Context triple: [John Jones, legalStatusOfUse, illegal]
-
A.
legalStatusInManyCountries
Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
-
B.
legalStatusVariesBy
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
C.
licenseStatus
Indicates the current state or condition of a license in relation to its validity, permissions, or compliance.
-
D.
legalStatusClarifiedBy
Indicates that the legal status of something is defined, explained, or resolved by a specific document, decision, or authoritative act.
-
E.
hasLegalStatus
chosen
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730f12a481908a27c15dc73987c6 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.