Triple
T27334790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Maddern |
E689910
|
entity |
| Predicate | precedesInJackLondonsMarriages |
P170966
|
FINISHED |
| Object | Charmian London |
—
|
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: Charmian London | Statement: [Elizabeth Maddern, precedesInJackLondonsMarriages, Charmian London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedesInJackLondonsMarriages Context triple: [Elizabeth Maddern, precedesInJackLondonsMarriages, Charmian London]
-
A.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
-
B.
resultedInMarriageTo
Indicates that one event, action, or circumstance led to or caused a marriage to occur between the related entities.
-
C.
houseByMarriage
Indicates a familial or household relationship established through marriage rather than by blood or direct residence.
-
D.
تاريخ الزواج
Indicates the date on which a marriage took place between the related entities.
-
E.
numberOfMarriagesOfSpouse
Indicates the total count of times the referenced spouse has been married.
- 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_69ef355e5b388190a8fc1eba9b4a6656 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 27, 2026, 11:40 a.m.