Triple
T26680494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Fagan |
E672593
|
entity |
| Predicate | victimEncountered |
P64161
|
FINISHED |
| Object | Queen Elizabeth II |
—
|
NE NERFINISHED |
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: Queen Elizabeth II | Statement: [Michael Fagan, victimEncountered, Queen Elizabeth II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimEncountered Context triple: [Michael Fagan, victimEncountered, Queen Elizabeth II]
-
A.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
-
B.
victimCategory
Indicates the classification or type of victim associated with an event, action, or harmful outcome.
-
C.
victimRole
chosen
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
D.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
-
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.
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_69eecda13424819092b17942c4edf722 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 3:19 a.m.