Triple
T690845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josiah Quincy Jr. |
E13387
|
entity |
| Predicate | legalAdvisorTo |
P5610
|
FINISHED |
| Object | Boston patriots |
—
|
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: Boston patriots | Statement: [Josiah Quincy Jr., legalAdvisorTo, Boston patriots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalAdvisorTo Context triple: [Josiah Quincy Jr., legalAdvisorTo, Boston patriots]
-
A.
legalRepresentation
Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
-
B.
legalProfessionRole
chosen
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
C.
legalSubject
Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
-
D.
legalTraining
Indicates that one entity has provided or received education or instruction in law from another entity.
-
E.
legalAct
Indicates that an entity performs, enacts, or is involved in a formal legal action, measure, or proceeding under a legal framework.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0aebde88190a49d421477713103 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d221d38819083c0adda81f59b07 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.