Triple
T13609882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joey Tribbiani |
E325159
|
entity |
| Predicate | hasDifficultyWith |
P110405
|
FINISHED |
| Object | learning French |
—
|
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: learning French | Statement: [Joey Tribbiani, hasDifficultyWith, learning French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifficultyWith Context triple: [Joey Tribbiani, hasDifficultyWith, learning French]
-
A.
hasDifficultyContext
Indicates that something’s difficulty is defined, interpreted, or constrained within a particular situational or contextual framework.
-
B.
hasDifficultyEffect
Indicates that one entity causes a change in the difficulty level or challenge associated with another entity or activity.
-
C.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
-
D.
difficulty
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
E.
hasDyslexia
Indicates that an entity experiences dyslexia, a learning difficulty affecting reading, writing, or spelling abilities.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbbb8c77dc8190b7bd803b5e168d23 |
completed | April 12, 2026, 3:34 p.m. |
Created at: April 9, 2026, 9:50 p.m.