Triple
T2575397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NATA |
E57762
|
entity |
| Predicate | assessmentLevel |
P39889
|
FINISHED |
| Object | census tract |
—
|
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: census tract | Statement: [NATA, assessmentLevel, census tract]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assessmentLevel Context triple: [NATA, assessmentLevel, census tract]
-
A.
achievementLevel
Indicates the degree or extent to which an entity has attained a particular goal, standard, or performance outcome.
-
B.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
C.
automationLevel
Indicates the degree to which a process, task, or system is performed automatically rather than manually.
-
D.
classificationLevel
Indicates the degree or tier within an ordered system or hierarchy to which something is assigned for categorization or control purposes.
-
E.
developmentLevel
Indicates the degree or stage of progress, advancement, or maturity that something has reached in its growth or evolution.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a43f188190a3d7538bf7867466 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:49 p.m.