Triple
T15270910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Junín |
E365016
|
entity |
| Predicate | hasProductionChallenges |
P83193
|
FINISHED |
| Object | high viscosity crude |
—
|
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: high viscosity crude | Statement: [Junín, hasProductionChallenges, high viscosity crude]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductionChallenges Context triple: [Junín, hasProductionChallenges, high viscosity crude]
-
A.
facedChallenges
chosen
Indicates that an entity has encountered and had to deal with difficulties, obstacles, or adverse conditions.
-
B.
developmentChallenges
Indicates difficulties, obstacles, or constraints that hinder or complicate the process of developing or improving something.
-
C.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
D.
troubledProduction
Indicates that the production process of a work (such as a film, show, or project) experienced significant difficulties, delays, or conflicts.
-
E.
hasEconomicChallenge
Indicates that an entity is experiencing or facing a financial or economic difficulty, constraint, or problem.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0094eac848190a1740ae1aa6b28e0 |
completed | April 15, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69deca90739081909bd1b797cdb8af2b |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:14 a.m.