Triple
T3228376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Bennet, 1st Earl of Arlington |
E67677
|
entity |
| Predicate | createdEarlDate |
P7360
|
FINISHED |
| Object | 1672 |
—
|
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: 1672 | Statement: [Henry Bennet, 1st Earl of Arlington, createdEarlDate, 1672]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createdEarlDate Context triple: [Henry Bennet, 1st Earl of Arlington, createdEarlDate, 1672]
-
A.
createdEarlBy
Indicates that an entity was granted or established as an earl by a specific creator or authority.
-
B.
createdAs
Indicates that one entity was originally made, designed, or brought into existence in the form, role, or identity specified by another entity.
-
C.
createdAtEvent
Indicates the specific event during which the entity was originally created.
-
D.
createdFor
Indicates that one entity was made, produced, or designed specifically to serve, benefit, or be used by another entity.
-
E.
createdAt
chosen
Indicates the date and time at which an entity was initially created or came into existence.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb6f8588190a33a9d6c779e8992 |
completed | March 8, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0dc2248190a38c40f4e06cd41c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.