Triple
T37214148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl of Ellenborough |
E922688
|
entity |
| Predicate | hasFirstHolderGivenName |
P3904
|
FINISHED |
| Object | Edward |
—
|
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: Edward | Statement: [Earl of Ellenborough, hasFirstHolderGivenName, Edward]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstHolderGivenName Context triple: [Earl of Ellenborough, hasFirstHolderGivenName, Edward]
-
A.
hasGivenNames
Indicates that an entity possesses one or more personal (given) names assigned to it.
-
B.
hasFirstHolder
chosen
Indicates that an entity is associated with the earliest or original holder (e.g., owner, position-bearer, or title-holder) of something.
-
C.
hasGivenNameTo
Indicates that one entity has assigned or provided a given (first) name to another entity.
-
D.
hasGivenNameWith
Indicates that an entity is associated with a specific given (first) name.
-
E.
secondHolderGivenName
Indicates that the given name specified belongs to the second holder in a multi-holder relationship or record.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a004b6ad4248190b402a0d01b0ebf83 |
completed | May 10, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_6a004ae736b881908a0efed8f63f982e |
completed | May 10, 2026, 9:07 a.m. |
Created at: May 3, 2026, 4:15 p.m.