Triple
T9193305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aouzou Strip |
E220640
|
entity |
| Predicate | militaryControlShiftedTo |
P82492
|
FINISHED |
| Object | Chad in late 1980s |
—
|
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: Chad in late 1980s | Statement: [Aouzou Strip, militaryControlShiftedTo, Chad in late 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryControlShiftedTo Context triple: [Aouzou Strip, militaryControlShiftedTo, Chad in late 1980s]
-
A.
militaryControl
Indicates that one entity exercises authoritative military power, command, or occupation over another entity or territory.
-
B.
wasMilitarized
Indicates that an entity underwent a process of being organized, equipped, or adapted for military use or purposes.
-
C.
belligerentControl
chosen
Indicates that one party exercises control, authority, or coercive influence over another in a hostile or conflict-oriented context.
-
D.
wasMilitarizedDuring
Indicates that an entity transitioned to or adopted a military character, role, or control during a specified time period or event.
-
E.
hasCivilianControl
Indicates that one party exercises authority or oversight over another in a civilian (non-military) capacity.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5c1fa9c8190bc5cc6dce8778694 |
completed | April 1, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.