Triple
T34965845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago high society |
E1008393
|
entity |
| Predicate | hadSocialNorms |
P182146
|
FINISHED |
| Object | strict etiquette |
—
|
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: strict etiquette | Statement: [Chicago high society, hadSocialNorms, strict etiquette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSocialNorms Context triple: [Chicago high society, hadSocialNorms, strict etiquette]
-
A.
attitudeTowardSocialNorms
Indicates an entity’s stance, feelings, or orientation regarding prevailing social rules, expectations, or norms.
-
B.
normativelyChallengedBy
Indicates that one entity’s norms, standards, or prescriptions are questioned, disputed, or opposed by another entity.
-
C.
levelOfNorm
Indicates the degree or extent to which something conforms to a specified norm, standard, or expected behavior.
-
D.
genderNorms
Indicates socially constructed expectations or rules about how individuals should behave, appear, or identify based on their perceived gender.
-
E.
hasReligiousNorm
Indicates that one entity prescribes, embodies, or is governed by a religious rule, standard, or expectation in relation to another entity or context.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.