Triple
T1136017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evanston, Illinois |
E23140
|
entity |
| Predicate | hasPolicyHistory |
P26431
|
FINISHED |
| Object | early adoption of temperance laws |
—
|
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: early adoption of temperance laws | Statement: [Evanston, Illinois, hasPolicyHistory, early adoption of temperance laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolicyHistory Context triple: [Evanston, Illinois, hasPolicyHistory, early adoption of temperance laws]
-
A.
hasCensorshipHistory
Indicates that an entity has previously been subject to censorship or involved in acts of censoring content.
-
B.
hasInflationHistory
Indicates that an entity is associated with a recorded or known pattern of inflation over time.
-
C.
hasWritingHistory
Indicates that an entity has a recorded history or log of its writing-related actions, changes, or authored content over time.
-
D.
hasDenominationHistory
Indicates that an entity has an associated record or sequence of changes in its denomination over time.
-
E.
hasVisitorPolicy
Indicates that an entity has an established policy governing the presence, behavior, or permissions of visitors.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bddfa598819088690e1ab010ba0b |
completed | March 1, 2026, 10:29 p.m. |
Created at: March 1, 2026, 7:44 p.m.