Triple
T4661125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYU Shanghai |
E102531
|
entity |
| Predicate | firstUndergraduateCohortEnrolled |
P50887
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [NYU Shanghai, firstUndergraduateCohortEnrolled, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUndergraduateCohortEnrolled Context triple: [NYU Shanghai, firstUndergraduateCohortEnrolled, 2013]
-
A.
hasTypicalFirstCohortSize
Indicates the usual or standard number of individuals in the first cohort associated with an entity.
-
B.
firstYear
Indicates that an entity is in its first year of existence, operation, or participation within a specified context.
-
C.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
D.
firstYearAsMajor
Indicates the year in which an entity first attained major status or classification.
-
E.
matriculationYear
chosen
Indicates the calendar year in which an individual formally enrolled or was admitted into an educational program or institution.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632a17cc8190bcdab0a13b89f5c0 |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.