Triple
T5868030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Enrollment Period |
E130444
|
entity |
| Predicate | hasStartMonth |
P6433
|
FINISHED |
| Object | January |
—
|
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: January | Statement: [General Enrollment Period, hasStartMonth, January]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStartMonth Context triple: [General Enrollment Period, hasStartMonth, January]
-
A.
hasMonth
chosen
Indicates that something is associated with, occurs in, or is assigned to a specific month.
-
B.
hasMonthCount
Indicates a relationship where an entity is associated with a specific number of months.
-
C.
hasMonthType
Indicates that something is associated with, classified by, or characterized as a particular type or category of month.
-
D.
hasVariableMonth
Indicates that something is associated with or occurs in a month that can change rather than being fixed.
-
E.
commandedAsFirstMonthIn
Indicates that an entity is designated or ordered to serve as the first month within a specified temporal system or context.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.