Triple
T28588385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fieschi assassination attempt |
E723571
|
entity |
| Predicate | notableVictimRank |
P870
|
FINISHED |
| Object | Marshal of France |
—
|
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: Marshal of France | Statement: [Fieschi assassination attempt, notableVictimRank, Marshal of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVictimRank Context triple: [Fieschi assassination attempt, notableVictimRank, Marshal of France]
-
A.
notableVictim
chosen
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
B.
notableVictims
Indicates that the object is a person or group who is especially well-known or significant as a victim of the subject.
-
C.
notableVictimNationality
Indicates that the relationship specifies the nationality of a notable victim associated with an event, incident, or action.
-
D.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
E.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, 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_69f01d7f92e481909847f5f3f3174a89 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a013d7180d08190b76f64cb430af9e1 |
completed | May 11, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_6a013c77d23c8190bb59e458b506d6e9 |
completed | May 11, 2026, 2:18 a.m. |
Created at: April 28, 2026, 4:19 a.m.