Triple
T25872279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glengarry bonnet |
E651790
|
entity |
| Predicate | typicalWearContext |
P104877
|
FINISHED |
| Object | parades |
—
|
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: parades | Statement: [Glengarry bonnet, typicalWearContext, parades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWearContext Context triple: [Glengarry bonnet, typicalWearContext, parades]
-
A.
typicalWear
chosen
Indicates that one entity is commonly or characteristically worn by the other in typical situations or contexts.
-
B.
individualWear
Indicates that an individual is wearing or has clothing or an accessory on their body.
-
C.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
D.
typicallyWornBy
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
-
E.
wearSchedule
Indicates a planned or prescribed pattern for when and how often something should be worn.
- 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_69e7ab3ad9d88190841ddcb93ab02e96 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: April 22, 2026, 8:11 a.m.