Triple
T22368052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uruguayan Clásico |
E552960
|
entity |
| Predicate | firstMeetingApproximateDate |
P147385
|
FINISHED |
| Object | early 20th century |
—
|
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 20th century | Statement: [Uruguayan Clásico, firstMeetingApproximateDate, early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetingApproximateDate Context triple: [Uruguayan Clásico, firstMeetingApproximateDate, early 20th century]
-
A.
dateOfFirstMeeting
Indicates the specific date on which two or more entities first met or came together.
-
B.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
C.
firstMeets
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
D.
firstMeetingYear
Indicates the calendar year in which two entities first met or had their initial encounter.
-
E.
firstIntroductionDate
Indicates the date on which an entity was first introduced or presented for the first 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580229688190a6e5e02b484033f7 |
completed | April 29, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69e73011e6388190a05edf137f488441 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e7342e9a0081909257210a81c96b29 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:44 p.m.