Triple
T14983943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro |
E373652
|
entity |
| Predicate | typicalArticle |
P116942
|
FINISHED |
| Object | "el" |
—
|
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: "el" | Statement: [Cerro, typicalArticle, "el"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalArticle Context triple: [Cerro, typicalArticle, "el"]
-
A.
articleType
Indicates the specific category or kind of article associated with an entity.
-
B.
articleContent
Indicates that one entity is the textual or media content that makes up the body of another entity, typically an article or document.
-
C.
articleOrParagraph
Indicates that one entity is either an entire article or a specific paragraph within an article in relation to another entity.
-
D.
keyArticle
Indicates that an article is a primary or central reference for understanding, supporting, or defining another entity or topic.
-
E.
notableArticle
Indicates that there exists an article or written work that is especially significant, prominent, or noteworthy in relation to the subject.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6ff4a7c8190ab7554f3a1a09b67 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:52 a.m.