Triple
T31139151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clan MacDonnell of Antrim |
E793731
|
entity |
| Predicate | intermarriage |
P4942
|
FINISHED |
| Object | intermarried with Gaelic Irish nobility |
—
|
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: intermarried with Gaelic Irish nobility | Statement: [Clan MacDonnell of Antrim, intermarriage, intermarried with Gaelic Irish nobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intermarriage Context triple: [Clan MacDonnell of Antrim, intermarriage, intermarried with Gaelic Irish nobility]
-
A.
marriesAcrossClassLines
Indicates entering into marriage with a partner from a different social or economic class than one’s own.
-
B.
marriedInto
chosen
Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
-
C.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
D.
involvesMarriage
Indicates that the relationship or action includes or is characterized by a marriage between the involved entities.
-
E.
marriesFor
Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: April 29, 2026, 9:05 p.m.