Triple
T8403957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Russell |
E198446
|
entity |
| Predicate | hasSpouseNotableFor |
P22220
|
FINISHED |
| Object | coverage of the Crimean War |
—
|
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: coverage of the Crimean War | Statement: [Harriet Russell, hasSpouseNotableFor, coverage of the Crimean War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseNotableFor Context triple: [Harriet Russell, hasSpouseNotableFor, coverage of the Crimean War]
-
A.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
B.
marriedToNotablePerson
Indicates that a person is legally married to another individual who is widely recognized or notable.
-
C.
spouseNotableAward
Indicates that a person’s spouse has received a notable award or honor.
-
D.
spouseNotableWorkField
chosen
Indicates that the notable work or professional field associated with a person’s spouse is being specified.
-
E.
spouseNotableAncestor
Indicates that a person’s spouse has an ancestor who is notable or historically significant.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb82505e0c81909549db59b7c4eb00 |
completed | March 31, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:04 p.m.