Triple
T19310917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five Points (Jacksonville) |
E482963
|
entity |
| Predicate | hasIntersectionOf |
P102344
|
FINISHED |
| Object | Park Street |
—
|
NE NERFINISHED |
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: Park Street | Statement: [Five Points (Jacksonville), hasIntersectionOf, Park Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntersectionOf Context triple: [Five Points (Jacksonville), hasIntersectionOf, Park Street]
-
A.
isIntersectionOf
chosen
Indicates that something is the exact common part shared by two or more other things, typically where they overlap or meet.
-
B.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
C.
overlapsWith
Indicates that two entities share a common part or region in space, time, or extent, but neither is completely contained within the other.
-
D.
hasSelfIntersection
Indicates that an entity (typically a curve or path) intersects or crosses itself at one or more points.
-
E.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cd270c819094fd2faa0681d2ad |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.