Triple
T2224841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calistoga City Council |
E48624
|
entity |
| Predicate | typeOfLawPassed |
P6890
|
FINISHED |
| Object | municipal ordinances |
—
|
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: municipal ordinances | Statement: [Calistoga City Council, typeOfLawPassed, municipal ordinances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawPassed Context triple: [Calistoga City Council, typeOfLawPassed, municipal ordinances]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
typeOfLegislation
Indicates the specific category or kind of legislation that a given legal act or measure belongs to.
-
C.
passedLegislation
chosen
Indicates that a governing body has formally approved and enacted a specific piece of legislation or law.
-
D.
signedIntoLawIn
Indicates that a proposed law or bill was formally approved and enacted by an authorized official in a specific place or jurisdiction.
-
E.
numberOfLaws
Indicates the quantitative count of laws associated with a given entity or context.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03ec3788190b5ae32201364f7ab |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.