Triple
T34917330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River of Sorrows |
E1007037
|
entity |
| Predicate | hasPrimaryLanguageOfToponym |
P193771
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [River of Sorrows, hasPrimaryLanguageOfToponym, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfToponym Context triple: [River of Sorrows, hasPrimaryLanguageOfToponym, Spanish]
-
A.
hasPrimaryLanguageForToponym
chosen
Indicates that a particular language is the main or official language used for the naming or labeling of a specific place name (toponym).
-
B.
hasLanguageOfToponym
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
C.
hasOfficialLanguageOfToponym
Indicates that a toponym is associated with an official language in which that place name is formally recognized or used.
-
D.
hasPrimaryEthnonym
Indicates that an entity is associated with its main or most commonly used ethnonym (ethnic group name) as its primary designation.
-
E.
hasWritingSystemOfToponym
Indicates that a toponym is written or represented using a particular writing system.
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a0340784c488190aa6c7c9be2e8a434 |
completed | May 12, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_6a033f33eddc819091507716f6ed7d7d |
completed | May 12, 2026, 2:54 p.m. |
Created at: May 3, 2026, 4 p.m.