Triple
T13589193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French preparatory classes |
E324646
|
entity |
| Predicate | economicTrackExample |
P110182
|
FINISHED |
| Object | ECE (économique et commerciale option économique) |
—
|
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: ECE (économique et commerciale option économique) | Statement: [French preparatory classes, economicTrackExample, ECE (économique et commerciale option économique)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicTrackExample Context triple: [French preparatory classes, economicTrackExample, ECE (économique et commerciale option économique)]
-
A.
economicTrend
Indicates the general direction or pattern of economic activity or conditions over a period of time.
-
B.
track
Indicates that one entity follows, monitors, or keeps a record of another entity’s state, behavior, or progress over time.
-
C.
technologyTrackExample
Indicates a relationship where one entity serves as an example or instance of a particular technology track associated with another entity.
-
D.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
E.
tracks
Indicates that one entity monitors, follows, or keeps a record of another entity’s state, behavior, or progress over time.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.