Triple
T3839393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abemama |
E93413
|
entity |
| Predicate | countryCapitalDistanceRelation |
P33891
|
FINISHED |
| Object | relatively close to Tarawa |
—
|
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: relatively close to Tarawa | Statement: [Abemama, countryCapitalDistanceRelation, relatively close to Tarawa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCapitalDistanceRelation Context triple: [Abemama, countryCapitalDistanceRelation, relatively close to Tarawa]
-
A.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
countryCapitalNearby
chosen
Indicates that a country’s capital city is geographically close to a specified location or entity.
-
C.
countryCapitalDistrict
Indicates that a specified district serves as the capital district (administrative capital area) of a given country.
-
D.
countryCapitalLocatedIn
Indicates that the capital city of a country is geographically situated within that country.
-
E.
countryCapitalContext
Indicates that one entity serves as the capital city of the specified country in a given contextual or temporal setting.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeb9f305c8190b71ac53bbb0c4beb |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.