Triple
T5722341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TU9 |
E126174
|
entity |
| Predicate | focusLevel |
P66078
|
FINISHED |
| Object | research-intensive universities |
—
|
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: research-intensive universities | Statement: [TU9, focusLevel, research-intensive universities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusLevel Context triple: [TU9, focusLevel, research-intensive universities]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
focusPosition
Indicates the spatial or logical position at which attention, concentration, or processing is currently directed within a given context.
-
C.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
D.
focusModel
Indicates that one entity serves as the primary or central model that another entity is directed toward, based on, or concentrated on.
-
E.
affectedLevel
Indicates the degree or extent to which one entity is impacted or influenced by another entity or event.
- 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c47f4c81909e6849c3be3e951c |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c028fec2bc819083f5dca6a8d9d435 |
completed | March 22, 2026, 5:38 p.m. |
Created at: March 22, 2026, 3:46 p.m.