Triple
T1643232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dukes of Marlborough |
E35519
|
entity |
| Predicate | familySeatGiftedFor |
P29780
|
FINISHED |
| Object | victory at the Battle of Blenheim |
—
|
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: victory at the Battle of Blenheim | Statement: [Dukes of Marlborough, familySeatGiftedFor, victory at the Battle of Blenheim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familySeatGiftedFor Context triple: [Dukes of Marlborough, familySeatGiftedFor, victory at the Battle of Blenheim]
-
A.
familySeat
Indicates the traditional principal residence or ancestral home associated with a particular family or lineage.
-
B.
giftBrought
Indicates that one entity brought or presented a gift to another entity.
-
C.
fareDiscount
Indicates that a reduced price is applied to a standard fare for a product or service.
-
D.
giftedBy
Indicates that one entity has given or presented another entity as a gift to a recipient.
-
E.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a9192f975c8190bfd514a4b5a8786c |
completed | March 5, 2026, 5:48 a.m. |
Created at: March 4, 2026, 7:28 p.m.