Triple
T33869685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attica Prison uprising |
E868165
|
entity |
| Predicate | areaSeized |
P177493
|
FINISHED |
| Object | D-yard of Attica Correctional Facility |
—
|
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: D-yard of Attica Correctional Facility | Statement: [Attica Prison uprising, areaSeized, D-yard of Attica Correctional Facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaSeized Context triple: [Attica Prison uprising, areaSeized, D-yard of Attica Correctional Facility]
-
A.
areaProtected
Indicates that a specified geographic area is designated and managed as protected, typically restricting certain activities to conserve its natural or cultural resources.
-
B.
acquiredLandArea
Indicates the total area of land that has been obtained or taken possession of through an acquisition.
-
C.
grantedLandArea
Indicates that a specific area of land has been formally allocated or given by one party to another.
-
D.
seizedCapital
Indicates that one entity forcibly took control of another entity’s capital city.
-
E.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69f6fcc44af48190b95fb9e12480a85f |
completed | May 3, 2026, 7:44 a.m. |
Created at: May 1, 2026, 1:47 a.m.