Triple
T13427710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jesús María Cora |
E313525
|
entity |
| Predicate | spokenInLocality |
P109887
|
FINISHED |
| Object | rural areas around Jesús María |
—
|
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: rural areas around Jesús María | Statement: [Jesús María Cora, spokenInLocality, rural areas around Jesús María]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInLocality Context triple: [Jesús María Cora, spokenInLocality, rural areas around Jesús María]
-
A.
spokenInLocalGovernmentArea
Indicates that a particular language or dialect is used or spoken within the jurisdiction of a specific local government area.
-
B.
spokenInCounty
Indicates that a particular language or dialect is spoken within the geographic area of a specified county.
-
C.
speaksIn
Indicates that an entity uses or expresses itself in a particular language or medium when speaking.
-
D.
spokenInPrefecture
Indicates that a particular language or dialect is spoken within the geographic area of a specified prefecture.
-
E.
spokenInCountryColloquialLanguage
Indicates that a language is informally or colloquially spoken within a particular country.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.