Triple
T37840830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Hartnell (vintage gown loaned by Queen Elizabeth II) |
E943469
|
entity |
| Predicate | laterWearer |
P203277
|
FINISHED |
| Object | Princess Beatrice |
—
|
NE NERFINISHED |
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: Princess Beatrice | Statement: [Norman Hartnell (vintage gown loaned by Queen Elizabeth II), laterWearer, Princess Beatrice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterWearer Context triple: [Norman Hartnell (vintage gown loaned by Queen Elizabeth II), laterWearer, Princess Beatrice]
-
A.
laterWielder
Indicates that one entity becomes the wielder or user of an object or power after another entity who wielded it earlier.
-
B.
temporarilyWornBy
Indicates that an item is being worn by an entity for a limited or non-permanent period of time.
-
C.
isWornAfter
Indicates that one item of clothing or accessory is put on later in time than another item.
-
D.
wearerMayRetain
Indicates that the wearer is allowed to keep or continue possessing the item in question.
-
E.
primaryWearer
Indicates that one entity is the main or principal user or wearer of another entity (such as an item or garment).
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a01487b73488190954eb5143e6f246e |
completed | May 11, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_6a0145210ae481908da59b02efdbc397 |
completed | May 11, 2026, 2:55 a.m. |
| PDg | Predicate description generation | batch_6a01487ac3608190946beee970e5559b |
completed | May 11, 2026, 3:09 a.m. |
Created at: May 3, 2026, 4:19 p.m.