Triple
T2201060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panama City Beach Parkway |
E50489
|
entity |
| Predicate | hasSegmentDescription |
P11875
|
FINISHED |
| Object | on some western segments |
—
|
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: on some western segments | Statement: [Panama City Beach Parkway, hasSegmentDescription, on some western segments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSegmentDescription Context triple: [Panama City Beach Parkway, hasSegmentDescription, on some western segments]
-
A.
hasDescription
chosen
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
B.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
C.
hasNotableSegment
Indicates that an entity includes or contains a specific segment, part, or portion that is considered notable or significant in some way.
-
D.
hasLevelDescription
Indicates that an entity is associated with a textual description specifying its level, degree, or stage.
-
E.
hasMultipleSegments
Indicates that the referenced entity is composed of more than one distinct segment or section.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa06bb4819092d7021358846e5f |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.