Triple
T33869707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attica Prison uprising |
E868165
|
entity |
| Predicate | inmateFatalities |
P130516
|
FINISHED |
| Object | 29 |
—
|
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: 29 | Statement: [Attica Prison uprising, inmateFatalities, 29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inmateFatalities Context triple: [Attica Prison uprising, inmateFatalities, 29]
-
A.
diedInCustodyOf
Indicates that an individual died while under the control, supervision, or physical custody of a specified authority or entity.
-
B.
deathRowIncarceration
Indicates that an individual is incarcerated in prison under a death sentence, awaiting execution.
-
C.
lastInmateDeath
Indicates the date or event of the most recent death of an inmate within a given facility, system, or context.
-
D.
numberSentencedToDeath
Indicates the number of individuals who have been formally sentenced to receive the death penalty.
-
E.
causedFatalities
chosen
Indicates that the referenced event or action directly resulted in one or more deaths.
- 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_69f700a6ff548190b98829c0a623b75f |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5a4f7881909324eb3c20ca96f1 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.