Triple
T32407713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bottom, Saba |
E828127
|
entity |
| Predicate | largestSettlementOf |
P171223
|
FINISHED |
| Object | Saba |
—
|
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: Saba | Statement: [The Bottom, Saba, largestSettlementOf, Saba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestSettlementOf Context triple: [The Bottom, Saba, largestSettlementOf, Saba]
-
A.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
B.
largestByPopulationIn
chosen
Indicates that an entity is the one with the greatest population among all entities within a specified area or group.
-
C.
largestUrbanConcentrationIn
Indicates that an entity represents the biggest or most populous urban area located within a specified geographic region.
-
D.
isLargestTownOn
Indicates that one town is the largest (by size, population, or another defined measure) among all towns located on a specified geographic feature or area.
-
E.
isLargestCityIn
Indicates that one city has the greatest population or size compared to all other cities within a specified region or administrative area.
- 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_69f34919f300819092b541c6277cd68a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c24ca0f08190a5b2c1d32205eaee |
completed | May 3, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:53 a.m.