Triple
T37542001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Road 700 |
E933349
|
entity |
| Predicate | hasNonContiguousSegmentsFollowing |
P29207
|
FINISHED |
| Object | U.S. Route 98 corridor |
E152508
|
NE 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: U.S. Route 98 corridor | Statement: [State Road 700, hasNonContiguousSegmentsFollowing, U.S. Route 98 corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonContiguousSegmentsFollowing Context triple: [State Road 700, hasNonContiguousSegmentsFollowing, U.S. Route 98 corridor]
-
A.
hasSuccessorSegment
Indicates that one segment directly follows another segment in a sequence or ordered structure.
-
B.
isNonContiguous
chosen
Indicates that the related elements are separated by one or more gaps and do not form a single continuous sequence or region.
-
C.
hasContinuousSequence
Indicates that there exists an unbroken, ordered sequence or range connecting the related entities without gaps.
-
D.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
-
E.
hasContinuation
Indicates that one entity serves as a continuation or subsequent part of another entity in a sequence or process.
- F. None of above.
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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40ba3dd2e881908b0a846ad55a8066 |
completed | June 28, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.