Triple
T31698676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam Halpert |
E808987
|
entity |
| Predicate | artSchoolAttendance |
P152318
|
FINISHED |
| Object | New York City art program |
—
|
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: New York City art program | Statement: [Pam Halpert, artSchoolAttendance, New York City art program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artSchoolAttendance Context triple: [Pam Halpert, artSchoolAttendance, New York City art program]
-
A.
homeAttendanceRecord
Indicates that an entity’s record or log of attendance is specifically associated with events or activities held at its home venue or location.
-
B.
attendanceIssues
Indicates that there are problems or irregularities related to an entity’s attendance, such as frequent absences, tardiness, or non-compliance with attendance expectations.
-
C.
attendanceFeature
Indicates that an entity provides or is associated with a feature or functionality related to attendance (such as tracking, managing, or recording attendance).
-
D.
attendance
Indicates the relationship between an event and the people who are present at or participate in that event.
-
E.
attendsClass
chosen
Indicates that an entity is present at and participates in a particular class or course session.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:11 p.m.