Triple
T18043773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manx advocates |
E431719
|
entity |
| Predicate | maySpecialiseIn |
P466
|
FINISHED |
| Object | commercial law |
—
|
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: commercial law | Statement: [Manx advocates, maySpecialiseIn, commercial law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maySpecialiseIn Context triple: [Manx advocates, maySpecialiseIn, commercial law]
-
A.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
B.
isSpecializedFor
Indicates that one entity is specifically adapted, designed, or focused to perform optimally for a particular function, context, or domain associated with another entity.
-
C.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
D.
laterSpecializedIn
Indicates that an entity initially engaged in a broader or different field and subsequently focused its work or expertise in a more specific or specialized area.
-
E.
allowsSpecializationIn
Indicates that one entity grants permission or provides the option for another entity to pursue a specific specialization within it.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff072508190a4065e3f83997aa9 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.