Triple
T8931946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montserrado County |
E212676
|
entity |
| Predicate | areaRankInLiberia |
P86251
|
FINISHED |
| Object | smallest by area |
—
|
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: smallest by area | Statement: [Montserrado County, areaRankInLiberia, smallest by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankInLiberia Context triple: [Montserrado County, areaRankInLiberia, smallest by area]
-
A.
populationRankInLuxembourg
Indicates the relative position of a place in Luxembourg when ordered by the size of its population.
-
B.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
C.
countryRankingContext
Indicates the contextual framework or criteria under which a country's ranking is determined or interpreted.
-
D.
capacityRankInWorld
Indicates the relative position or ranking of an entity’s capacity compared to all similar entities worldwide.
-
E.
areaRankingInChad
Indicates the relative position of an entity in a size-based ranking specifically within the geographic context of Chad.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668e5c108190b08f9cd6b4fd4a8b |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc608331f88190bcb500ff63527f8a |
completed | April 1, 2026, 12:02 a.m. |
Created at: March 30, 2026, 6:57 p.m.