Triple
T27431817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamplonita River |
E690661
|
entity |
| Predicate | hasMiddleCourseIn |
P174253
|
FINISHED |
| Object | Cúcuta municipality |
—
|
NE NERFINISHED |
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: Cúcuta municipality | Statement: [Pamplonita River, hasMiddleCourseIn, Cúcuta municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMiddleCourseIn Context triple: [Pamplonita River, hasMiddleCourseIn, Cúcuta municipality]
-
A.
hasUpperCourseIn
Indicates that the upper (initial) part of a river or watercourse lies within or flows through a specified geographic area or region.
-
B.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
C.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
D.
hasTastingMenu
Indicates that an establishment offers a predefined multi-course tasting menu as part of its dining options.
-
E.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
- 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 27, 2026, 12:42 p.m.