Triple
T33380331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaumains |
E854754
|
entity |
| Predicate | firstGiftRequested |
P206439
|
FINISHED |
| Object | food and drink for a year |
—
|
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: food and drink for a year | Statement: [Beaumains, firstGiftRequested, food and drink for a year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstGiftRequested Context triple: [Beaumains, firstGiftRequested, food and drink for a year]
-
A.
thirdGiftRequested
Indicates that an entity has requested a third gift from another entity or source.
-
B.
secondGiftRequested
Indicates that a request has been made for an additional (second) gift beyond the initial one.
-
C.
firstDayGift
Indicates that one entity gives or receives a gift associated with the first day of an event, period, or relationship.
-
D.
intendedGiftFor
Indicates that something is meant or designated to be given as a gift to a particular recipient.
-
E.
typeOfGift
Indicates the specific kind or category of gift involved in a giving or gifting relationship.
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:35 a.m.