Triple
T25672688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krajina region |
E643719
|
entity |
| Predicate | preWarPopulationCharacteristic |
P157967
|
FINISHED |
| Object | Serb-majority |
—
|
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: Serb-majority | Statement: [Krajina region, preWarPopulationCharacteristic, Serb-majority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preWarPopulationCharacteristic Context triple: [Krajina region, preWarPopulationCharacteristic, Serb-majority]
-
A.
historicalPopulationCharacteristic
Indicates a relationship where an entity is associated with a demographic or population-related attribute that held true during a specific historical period.
-
B.
preWarEthnicComposition
chosen
Indicates the ethnic makeup or distribution of ethnic groups in a place or population before a specific war or armed conflict.
-
C.
preWarCharacter
Indicates that a character existed or had a particular state or role prior to a specified war or conflict.
-
D.
preWarCountry
Indicates that a country existed or held a particular status prior to a specified war or major armed conflict.
-
E.
formerPopulation
Indicates that an entity once had a certain population value or size during a past time period but no longer does.
- 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_69e77e7f69808190ad27df1006f6037a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fb3460488190a720fe1f708509f2 |
completed | May 2, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 7:30 p.m.