Triple
T30369512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RADSL |
E772511
|
entity |
| Predicate | adjustmentBasedOn |
P112148
|
FINISHED |
| Object | Line conditions |
—
|
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: Line conditions | Statement: [RADSL, adjustmentBasedOn, Line conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjustmentBasedOn Context triple: [RADSL, adjustmentBasedOn, Line conditions]
-
A.
adjustmentType
Indicates the specific kind or category of modification applied to an existing value, state, or configuration within the relationship.
-
B.
adjustsFor
chosen
Indicates that one entity modifies, compensates, or accounts for the effects of another entity to achieve a corrected or normalized result.
-
C.
basedOnSetting
Indicates that one entity is derived from, influenced by, or constructed using the setting or contextual environment defined by another entity.
-
D.
basedOnBy
Indicates that one entity is derived from, justified by, or constructed using another entity as its source, foundation, or reference.
-
E.
basedOnAdaptationsOf
Indicates that something is derived from or created using one or more prior adaptations of an original work, rather than directly from the original source.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682825f408190b6510f20015c4e52 |
completed | May 2, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:59 p.m.