Triple
T33869710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attica Prison uprising |
E868165
|
entity |
| Predicate | causeOfMostDeaths |
P144
|
FINISHED |
| Object | gunfire by state forces |
—
|
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: gunfire by state forces | Statement: [Attica Prison uprising, causeOfMostDeaths, gunfire by state forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfMostDeaths Context triple: [Attica Prison uprising, causeOfMostDeaths, gunfire by state forces]
-
A.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
C.
deathCausesPlot
Indicates that a character’s death serves as a driving cause or catalyst for the development of the plot.
-
D.
riskFactorForDeath
Indicates that something increases the likelihood or probability of death occurring.
-
E.
reasonForDemise
Indicates the cause, circumstance, or factor that led to an entity’s death or termination.
- 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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: May 1, 2026, 1:47 a.m.