Triple
T3857179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transportation Research and Analysis Computing Center |
E90045
|
entity |
| Predicate | typeOfComputation |
P37649
|
FINISHED |
| Object | modeling |
—
|
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: modeling | Statement: [Transportation Research and Analysis Computing Center, typeOfComputation, modeling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfComputation Context triple: [Transportation Research and Analysis Computing Center, typeOfComputation, modeling]
-
A.
computationalClass
Indicates that two entities share the same computational complexity class or that one entity is categorized within a specified computational complexity class.
-
B.
computes
Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
-
C.
computingModel
chosen
Indicates the computational framework, paradigm, or formal system used to perform or describe a computation.
-
D.
typeOfOperation
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
E.
usesComputationMethod
Indicates that an entity performs its processing or decision-making by applying a specified computational method or algorithm.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec09312c81908ffd7441c83730c8 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.