Triple
T33453393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorenzino de' Medici |
E856703
|
entity |
| Predicate | victimWas |
P177410
|
FINISHED |
| Object | first Duke of Florence |
—
|
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: first Duke of Florence | Statement: [Lorenzino de' Medici, victimWas, first Duke of Florence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimWas Context triple: [Lorenzino de' Medici, victimWas, first Duke of Florence]
-
A.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
-
B.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
C.
victimTitle
Indicates that one entity holds a title, role, or designation specifically in the capacity of being a victim in relation to another entity or event.
-
D.
victimHeirTo
Indicates that the victim is the legal heir or inheritor of another person involved in the event or relationship.
-
E.
victimStatus
Indicates the condition or state of a person who has been harmed or wronged as a result of an event, action, or offense.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb93224881908fc66fe76115fcdb |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fb17d5ec81909091e37e1ddbe577 |
completed | May 3, 2026, 7:36 a.m. |
Created at: May 1, 2026, 1:37 a.m.