Triple
T13599143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | assassination of Leon Trotsky |
E324897
|
entity |
| Predicate | victimResidence |
P101215
|
FINISHED |
| Object | fortified house in Coyoacán |
—
|
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: fortified house in Coyoacán | Statement: [assassination of Leon Trotsky, victimResidence, fortified house in Coyoacán]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimResidence Context triple: [assassination of Leon Trotsky, victimResidence, fortified house in Coyoacán]
-
A.
hasVictimResidence
chosen
Indicates that a specified location is the place where the victim resides or lived.
-
B.
victimState
Indicates the condition or status that a victim is in as a result of an event, action, or harmful incident.
-
C.
victimStatus
Indicates the condition or state of a person who has been harmed or wronged as a result of an event, action, or offense.
-
D.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
E.
victimGroupContext
Indicates the contextual circumstances or setting in which a victim group is targeted, affected, or involved in an event or action.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0795acc8190a08667ab9dcb0d44 |
completed | April 12, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.