Triple
T13952164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel |
E335552
|
entity |
| Predicate | typicalNameDay |
P83423
|
FINISHED |
| Object | 29 September (Saint Michael) |
—
|
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: 29 September (Saint Michael) | Statement: [Michel, typicalNameDay, 29 September (Saint Michael)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNameDay Context triple: [Michel, typicalNameDay, 29 September (Saint Michael)]
-
A.
namesDay
Indicates that one entity is the name assigned to a particular day (such as a weekday or holiday) associated with another entity.
-
B.
day1Name
Indicates the name or label assigned to the first day in a sequence or schedule.
-
C.
dayName
Indicates the specific name of the day of the week associated with a given date or time.
-
D.
nameDayCalendar
chosen
Indicates a calendar system that specifies which personal names are celebrated on particular days (name days).
-
E.
nameDayStatus
Indicates the status or condition of a person's name day (e.g., whether it is set, active, upcoming, or celebrated).
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e146720819085d0f5eae558b7a4 |
completed | April 14, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.