Triple
T27494768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TZ |
E693993
|
entity |
| Predicate | denotesCountryWithLargestCity |
P162667
|
FINISHED |
| Object | Dar es Salaam |
—
|
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: Dar es Salaam | Statement: [TZ, denotesCountryWithLargestCity, Dar es Salaam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denotesCountryWithLargestCity Context triple: [TZ, denotesCountryWithLargestCity, Dar es Salaam]
-
A.
countryLargestCityOfSee
Indicates that a country is associated with the largest city of a specified administrative or geographic entity (such as a region, state, or territory).
-
B.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
C.
capitalIsLargestCity
Indicates that the capital city of a region or country is also its most populous or largest city.
-
D.
areLargestCitiesOf
Indicates that the subject entities are the largest cities within the regions or countries specified by the object entities.
-
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. 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_69ef5382b9648190be0b1ef2ad5d043c |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62e8cb0c48190bbd8647a1fb6635b |
completed | May 2, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62cd1912c8190ab3f3288442115a4 |
completed | May 2, 2026, 4:56 p.m. |
Created at: April 27, 2026, 1:07 p.m.