Triple
T20652776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mon credo |
E507540
|
entity |
| Predicate | followsChronologyOf |
P104670
|
FINISHED |
| Object | Mireille Mathieu singles |
—
|
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: Mireille Mathieu singles | Statement: [Mon credo, followsChronologyOf, Mireille Mathieu singles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsChronologyOf Context triple: [Mon credo, followsChronologyOf, Mireille Mathieu singles]
-
A.
followsInReleaseChronology
chosen
Indicates that one entity is released after another in a chronological sequence of releases.
-
B.
chronologicallyOrdered
Indicates that the related entities are arranged in the order in which they occur in time.
-
C.
chronologicallyAfter
Indicates that one event or state occurs later in time than another.
-
D.
chronologicallyCovers
Indicates that one time period, event, or sequence extends over and includes the entire chronological span of another.
-
E.
chronologicallyOrders
Indicates that one entity arranges or sequences other entities according to their positions in time, from earlier to later.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af22d6bc8190b9d6877aba5704eb |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.