Triple
T38405182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miami street grid |
E901005
|
entity |
| Predicate | hasExceptionAreas |
P55251
|
FINISHED |
| Object | waterfront neighborhoods |
—
|
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: waterfront neighborhoods | Statement: [Miami street grid, hasExceptionAreas, waterfront neighborhoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExceptionAreas Context triple: [Miami street grid, hasExceptionAreas, waterfront neighborhoods]
-
A.
notableExceptionArea
chosen
Indicates that a specific area is recognized as an exception to a general rule, pattern, or classification that applies elsewhere.
-
B.
hasExceptionRule
Indicates that a general rule or condition is overridden or modified by a specific exception rule in this context.
-
C.
hasException
Indicates that a general rule, process, or condition does not apply in a particular case due to a specified exception.
-
D.
hasExceptionFor
Indicates that a general rule, condition, or behavior does not apply in a particular case or under specific circumstances.
-
E.
hasEnforcementArea
Indicates that an entity is subject to or associated with a specific geographic or jurisdictional area where certain rules, regulations, or enforcement actions apply.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: May 3, 2026, 4:31 p.m.