Triple
T285026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman legion |
E5868
|
entity |
| Predicate | hasTypicalFirstCohortSize |
P10333
|
FINISHED |
| Object | larger than other cohorts |
—
|
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: larger than other cohorts | Statement: [Roman legion, hasTypicalFirstCohortSize, larger than other cohorts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalFirstCohortSize Context triple: [Roman legion, hasTypicalFirstCohortSize, larger than other cohorts]
-
A.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
B.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
D.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
E.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a2605b372c8190831570aa6532cc96 |
completed | Feb. 28, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69a25b7a8d148190aacdcc8ccb35c7f3 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a2605a3d988190a8872169fd8eb2e8 |
completed | Feb. 28, 2026, 3:26 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.