Triple
T36492650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Arbor Fire Department |
E899090
|
entity |
| Predicate | policyProcess |
P192329
|
FINISHED |
| Object | subject to council resolutions |
—
|
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: subject to council resolutions | Statement: [Ann Arbor Fire Department, policyProcess, subject to council resolutions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyProcess Context triple: [Ann Arbor Fire Department, policyProcess, subject to council resolutions]
-
A.
policyApproach
Indicates the strategy, method, or overall course of action adopted in creating, implementing, or managing a policy.
-
B.
policyInput
Indicates that a policy is being provided as input or applied as an influencing factor to another entity or process.
-
C.
policyModel
Indicates a relationship where an entity serves as, or is governed by, a particular policy model that defines rules, strategies, or decision-making behavior.
-
D.
policyElement
Indicates that something is a component or constituent part of a broader policy.
-
E.
policyMaker
Indicates that an entity plays a role in creating, shaping, or deciding policies that govern or guide others.
- F. None of above. chosen
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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
| PDg | Predicate description generation | batch_69fd05b965608190a3666410b9f8e125 |
completed | May 7, 2026, 9:35 p.m. |
Created at: May 3, 2026, 4:10 p.m.