Triple
T17023369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald FitzGerald, 9th Duke of Leinster |
E413000
|
entity |
| Predicate | hasNoblePrecedence |
P125544
|
FINISHED |
| Object | first among dukes in the Peerage of Ireland |
—
|
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: first among dukes in the Peerage of Ireland | Statement: [Gerald FitzGerald, 9th Duke of Leinster, hasNoblePrecedence, first among dukes in the Peerage of Ireland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoblePrecedence Context triple: [Gerald FitzGerald, 9th Duke of Leinster, hasNoblePrecedence, first among dukes in the Peerage of Ireland]
-
A.
hasNoble
Indicates that one entity possesses or is associated with a noble title, status, or noble individual.
-
B.
hasNobleStatus
Indicates that an entity possesses a recognized noble rank, title, or aristocratic status.
-
C.
nobleRankAbove
Indicates that one entity holds a higher noble rank or title in a hierarchy than another entity.
-
D.
evaluatesAsNoble
Indicates that an entity is judged or classified as having noble status or qualities.
-
E.
confersPrecedenceIn
Indicates that one entity is granted higher priority, rank, or standing over another within a specified context or domain.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d2abbc81908943becf5f539fc6 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:33 a.m.