Triple
T30094191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Enclosure |
E764817
|
entity |
| Predicate | hasDressCodeRule |
P2738
|
FINISHED |
| Object | no fascinators in place of hats (traditional rule) |
—
|
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: no fascinators in place of hats (traditional rule) | Statement: [Royal Enclosure, hasDressCodeRule, no fascinators in place of hats (traditional rule)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDressCodeRule Context triple: [Royal Enclosure, hasDressCodeRule, no fascinators in place of hats (traditional rule)]
-
A.
hasDressCode
chosen
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
B.
hasDressNumber
Indicates that an entity (typically a player or performer) is associated with a specific dress or jersey number.
-
C.
wearingConvention
Indicates that an entity is dressed in accordance with a particular convention, style, or dress code.
-
D.
hasVenueRules
Indicates that specific rules or policies are associated with, or apply to, a particular venue.
-
E.
hasDressCircle
Indicates that something (typically a theater or venue) includes or is equipped with a dress circle seating area.
- 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d8e989081909d062bcf86c82ca2 |
completed | May 2, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:06 p.m.