Triple
T2205921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transportation Services Index |
E50795
|
entity |
| Predicate | adjustedFor |
P17138
|
FINISHED |
| Object | seasonal variation |
—
|
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: seasonal variation | Statement: [Transportation Services Index, adjustedFor, seasonal variation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjustedFor Context triple: [Transportation Services Index, adjustedFor, seasonal variation]
-
A.
notAdjustedFor
Indicates that a value, measure, or result has not been modified or corrected to account for certain factors, conditions, or variables.
-
B.
adjustmentType
Indicates the specific kind or category of modification applied to an existing value, state, or configuration within the relationship.
-
C.
adjustedFrontier
Indicates that a boundary or limit between entities has been modified or recalibrated from its previous position or state.
-
D.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
E.
calibratedFor
chosen
Indicates that something has been adjusted or tuned to operate accurately or optimally for a specific target, condition, or context.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.