Triple
T5975945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coque |
E132990
|
entity |
| Predicate | countryCapitalOfContainingCity |
P67826
|
FINISHED |
| Object | state capital of Pernambuco |
—
|
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: state capital of Pernambuco | Statement: [Coque, countryCapitalOfContainingCity, state capital of Pernambuco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCapitalOfContainingCity Context triple: [Coque, countryCapitalOfContainingCity, state capital of Pernambuco]
-
A.
cityAsCapitalOf
Indicates that a city serves as the official capital of a specified political or administrative entity.
-
B.
countryCapitalMunicipality
Indicates that a given municipality serves as the capital city of a specified country.
-
C.
regionCapital
Indicates that one entity is the capital city or administrative center of a specified region.
-
D.
countryCapitalLocatedOn
Indicates that the capital city of a country is situated on or directly adjacent to a specified geographic feature (such as a river, coast, or lake).
-
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. 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:04 p.m.