Triple
T34809762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dréan |
E1003464
|
entity |
| Predicate | countryDuringNameMondovi |
P41268
|
FINISHED |
| Object | French Algeria |
—
|
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: French Algeria | Statement: [Dréan, countryDuringNameMondovi, French Algeria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryDuringNameMondovi Context triple: [Dréan, countryDuringNameMondovi, French Algeria]
-
A.
countryDuring
chosen
Indicates that one entity exists, occurs, or is valid within the temporal span during which the other entity is recognized as a specific country.
-
B.
countryDuringMontenegrinKingdom
Indicates that a country existed or held that status during the historical period of the Montenegrin Kingdom.
-
C.
country1
Indicates that the subject entity is a country (or represents a country) in the given context.
-
D.
countryPortionIn
Indicates that a specific part or region is located within the boundaries of a particular country.
-
E.
countryExample
Indicates that one country serves as a representative or illustrative example of another country in a given context.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a017bc21b048190b9c680013de203b6 |
completed | May 11, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_6a017aa09c4481909c3b55e0cd13501e |
completed | May 11, 2026, 6:43 a.m. |
Created at: May 3, 2026, 3:59 p.m.