Triple
T3712185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Infanta Elena, Duchess of Lugo |
E81440
|
entity |
| Predicate | dateNobleTitleGranted |
P19179
|
FINISHED |
| Object | 1995-03-03 |
—
|
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: 1995-03-03 | Statement: [Infanta Elena, Duchess of Lugo, dateNobleTitleGranted, 1995-03-03]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateNobleTitleGranted Context triple: [Infanta Elena, Duchess of Lugo, dateNobleTitleGranted, 1995-03-03]
-
A.
nobleTitleCreationDate
Indicates the date on which a particular noble title was formally created or granted.
-
B.
nobleTitleStartDate
chosen
Indicates the date on which an entity first acquired or began holding a particular noble title.
-
C.
monarchWhoGrantedTitle
Indicates the monarch who conferred or bestowed a particular title upon an individual.
-
D.
dateOfKnighthood
Indicates the specific date on which an individual was formally granted knighthood.
-
E.
nobleTitleFrom
Indicates that a person derives or holds their noble title from a specified source, such as a place, lineage, or authority.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc58617bc8190bb712d1c90394215 |
completed | March 8, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.