Triple
T5564273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J’en ai marre! |
E145841
|
entity |
| Predicate | popularityPeriod |
P3813
|
FINISHED |
| Object | early 2000s |
—
|
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: early 2000s | Statement: [J’en ai marre!, popularityPeriod, early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularityPeriod Context triple: [J’en ai marre!, popularityPeriod, early 2000s]
-
A.
popularInPeriod
chosen
Indicates that something is widely liked, used, or influential during a specified time period.
-
B.
popularityContext
Indicates the situational or domain-specific setting in which something’s popularity or level of public favor is evaluated.
-
C.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
D.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
E.
popularityType
Indicates the specific category or nature of how popularity is characterized or measured in the relationship.
- 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_69c008fdae24819081aa002ad99cd966 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02032330c819094f2bc1e8c93a5b6 |
completed | March 22, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69c01b12826c8190969a584d0f53aa44 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.