Triple
T5034643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibb |
E113391
|
entity |
| Predicate | governorateRankByPopulation |
P1026
|
FINISHED |
| Object | one of the most populous governorates in Yemen |
—
|
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: one of the most populous governorates in Yemen | Statement: [Ibb, governorateRankByPopulation, one of the most populous governorates in Yemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governorateRankByPopulation Context triple: [Ibb, governorateRankByPopulation, one of the most populous governorates in Yemen]
-
A.
stateRank
Indicates the relative position or standing of an entity within a specific state-level ordering or hierarchy.
-
B.
rankByPopulationInUS
Indicates the relative ordering of entities based on the size of their populations within the United States.
-
C.
hasPopulationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
rankByPopulationInUnitedStates
Indicates the relative ordering of entities based on their population size within the United States.
-
E.
populationDensityRankInUS
Indicates the relative position of a place in a ranking of U.S. locations ordered by population density.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73b8646c8190b3cc20193e4639ee |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.