Triple
T3051918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | family of Mark Twain |
E83588
|
entity |
| Predicate | hasMarriage |
P45367
|
FINISHED |
| Object | Marriage of Mark Twain and Olivia Langdon (1870) |
—
|
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: Marriage of Mark Twain and Olivia Langdon (1870) | Statement: [family of Mark Twain, hasMarriage, Marriage of Mark Twain and Olivia Langdon (1870)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarriage Context triple: [family of Mark Twain, hasMarriage, Marriage of Mark Twain and Olivia Langdon (1870)]
-
A.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
-
B.
marriedBefore
Indicates that one entity entered into a marriage at an earlier time than the other entity.
-
C.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
D.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
-
E.
marriedInto
Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bf274f88190a759f9ce3da47c35 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad9b272a408190ba0ce09bdeea76c9 |
completed | March 8, 2026, 3:52 p.m. |
Created at: March 8, 2026, 3:01 p.m.