Triple
T9450697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances Annie Dyer |
E227880
|
entity |
| Predicate | spouseNotoriety |
P19181
|
FINISHED |
| Object | ordered the 1919 Jallianwala Bagh massacre in Amritsar |
—
|
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: ordered the 1919 Jallianwala Bagh massacre in Amritsar | Statement: [Frances Annie Dyer, spouseNotoriety, ordered the 1919 Jallianwala Bagh massacre in Amritsar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNotoriety Context triple: [Frances Annie Dyer, spouseNotoriety, ordered the 1919 Jallianwala Bagh massacre in Amritsar]
-
A.
spouseNotableFor
chosen
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
spouseAlsoKnownAs
Indicates that a person’s spouse is referred to by an alternative name or alias.
-
D.
spouseNotableAward
Indicates that a person’s spouse has received a notable award or honor.
-
E.
marriedToNotablePerson
Indicates that a person is legally married to another individual who is widely recognized or notable.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f6649a48190b6844daa6202efe5 |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.