Triple
T27978166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSZ |
E706544
|
entity |
| Predicate | hadInternalDivisions |
P63526
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [NSZ, hadInternalDivisions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadInternalDivisions Context triple: [NSZ, hadInternalDivisions, yes]
-
A.
hadInternalDivision
chosen
Indicates that an entity experienced a split or conflict within its own members, factions, or components.
-
B.
wasDividedBetween
Indicates that something was partitioned into portions that were allocated to two or more distinct recipients or groups.
-
C.
haveSocialDivision
Indicates that a group or society is organized into distinct social categories, classes, or divisions that differentiate its members.
-
D.
wasDividedFrom
Indicates that one entity was separated or split off from another entity, resulting in two distinct parts or groups.
-
E.
historicallyDividedInto
Indicates that an entity was separated into multiple distinct parts or regions during a past historical period.
- 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_69ef96b7f330819090f315318ba6977e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63b661b8081908abaf92cde6ab125 |
completed | May 2, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:42 p.m.