Triple
T34901674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adjumani District |
E1006606
|
entity |
| Predicate | hostsPopulationFrom |
P181844
|
FINISHED |
| Object | South Sudan |
—
|
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: South Sudan | Statement: [Adjumani District, hostsPopulationFrom, South Sudan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostsPopulationFrom Context triple: [Adjumani District, hostsPopulationFrom, South Sudan]
-
A.
hostsPopulation
Indicates that an entity serves as the living environment or container in which a particular population exists or resides.
-
B.
hadPopulationFrom
Indicates that an entity had a specified population value during a particular time period starting from a given date.
-
C.
hostedPopulationType
Indicates the type or category of population that is accommodated or supported by a given host entity.
-
D.
populationMethod
Indicates how a population is determined, measured, or derived for a given context or dataset.
-
E.
staffPopulationApprox
Indicates an approximate or estimated number of staff associated with an 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782cf61948190b98185d961609554 |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f782c848fc8190baea8c845ca9079f |
completed | May 3, 2026, 5:15 p.m. |
Created at: May 3, 2026, 4 p.m.