Triple
T442424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Patrick's Day |
E10139
|
entity |
| Predicate | typicalAttire |
P271
|
FINISHED |
| Object | green accessories |
—
|
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: green accessories | Statement: [St. Patrick's Day, typicalAttire, green accessories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAttire Context triple: [St. Patrick's Day, typicalAttire, green accessories]
-
A.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
B.
wears
chosen
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
C.
hasDressCode
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
D.
hasTypicalArmor
Indicates that an entity normally wears or is equipped with a standard or characteristic type of armor.
-
E.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef42b4008190abed9d79926c7022 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2edde2b9c8190bd20b582eb4c5065 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.