Triple
T5034578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiz |
E113390
|
entity |
| Predicate | populationRankingInYemen |
P1169
|
FINISHED |
| Object | among the largest cities 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: among the largest cities in Yemen | Statement: [Taiz, populationRankingInYemen, among the largest cities in Yemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankingInYemen Context triple: [Taiz, populationRankingInYemen, among the largest cities in Yemen]
-
A.
populationRankInSudan
Indicates the relative position of an entity in terms of population size compared to other entities within Sudan.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
D.
populationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
viewOnArabPopulation
Indicates a stance, opinion, or perspective that someone or something holds regarding the Arab population.
- 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.