Triple
T9309796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alkire-Foster method |
E223977
|
entity |
| Predicate | dimensionExample |
P5533
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [Alkire-Foster method, dimensionExample, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionExample Context triple: [Alkire-Foster method, dimensionExample, education]
-
A.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
B.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
C.
dimensionType
chosen
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
D.
dimensionVariant
Indicates a relationship where one entity is a variant or alternative version of another with respect to certain dimensions or configurable attributes.
-
E.
dimensionCharacteristic
Indicates that one entity specifies or describes a dimensional property or measurement characteristic of another entity.
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd20ac17488190aa6acf7a61420632 |
completed | April 1, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:37 p.m.