Triple
T25446979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clementia of Hungary |
E637662
|
entity |
| Predicate | monarchDuringReignAsQueenConsortOfFrance |
P59097
|
FINISHED |
| Object | Louis X of France |
—
|
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: Louis X of France | Statement: [Clementia of Hungary, monarchDuringReignAsQueenConsortOfFrance, Louis X of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monarchDuringReignAsQueenConsortOfFrance Context triple: [Clementia of Hungary, monarchDuringReignAsQueenConsortOfFrance, Louis X of France]
-
A.
reignAsQueenConsortOfFranceEnd
Indicates the time or event at which an individual’s tenure as queen consort of France comes to an end.
-
B.
reignAsQueenConsortOfFranceStart
Indicates the time at which a person began serving as queen consort of France.
-
C.
reignAsQueenConsortFrom
Indicates the time period during which a person held the role of queen consort, starting from a specified date or event.
-
D.
reignAsQueenConsort
chosen
Indicates that a person holds the position and performs the role of queen consort during the reign of a monarch.
-
E.
marriedToMonarchFrom
Indicates that a person is married to a monarch who rules or comes from a specified country or region.
- 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f70455f48190b23c09dbed884015 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 2:02 p.m.