Triple
T36836598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Haiti (North) |
E910287
|
entity |
| Predicate | regnalNameOfHolder |
P34139
|
FINISHED |
| Object | Henri I |
—
|
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: Henri I | Statement: [King of Haiti (North), regnalNameOfHolder, Henri I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regnalNameOfHolder Context triple: [King of Haiti (North), regnalNameOfHolder, Henri I]
-
A.
titleHolderName
chosen
Indicates the name of the person or entity that holds a particular title or position.
-
B.
titleHolderFullName
Indicates the full personal name of the entity that holds a particular title or position.
-
C.
correspondsToReignTitleHolder
Indicates that a given reign or period of rule is associated with, and held by, a specific title holder.
-
D.
secondHolderGivenName
Indicates that the given name specified belongs to the second holder in a multi-holder relationship or record.
-
E.
regnalNameAsPretender
Indicates the name a person uses as a claimed ruler or monarch while not officially recognized as holding that throne.
- 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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.