Triple
T23804414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Rampton |
E589662
|
entity |
| Predicate | caseTypeSpecialization |
P153620
|
FINISHED |
| Object | defamation |
—
|
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: defamation | Statement: [Richard Rampton, caseTypeSpecialization, defamation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseTypeSpecialization Context triple: [Richard Rampton, caseTypeSpecialization, defamation]
-
A.
branchSpecialization
Indicates that one branch or subdivision is specialized or focused in a particular area, function, or domain relative to others.
-
B.
exportSpecialization
Indicates a relationship where one entity specializes in exporting particular goods, services, or resources to another entity or market.
-
C.
specialCaseOf
Indicates that one entity represents a more specific, exceptional, or restricted instance of the general situation, rule, or relationship expressed by another entity.
-
D.
propertyTypeSpecialization
Indicates that one property type is a more specific or specialized version of another, more general property type.
-
E.
laterSpecialization
Indicates that one entity becomes a more specialized or refined version of another entity at a later point in time.
- F. None of above. chosen
Provenance (4 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_69e25d19fecc8190a5cf39bbb18d5d7f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c750048c8190899ff611df35b361 |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:55 p.m.