Triple
T15144528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir John Shore |
E361771
|
entity |
| Predicate | createdBaronTeignmouth |
P39376
|
FINISHED |
| Object | 1798 |
—
|
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: 1798 | Statement: [Sir John Shore, createdBaronTeignmouth, 1798]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createdBaronTeignmouth Context triple: [Sir John Shore, createdBaronTeignmouth, 1798]
-
A.
createdBaronet
Indicates that one entity formally established or granted a baronetcy title to another entity.
-
B.
createdBaronOrBaronessOf
chosen
Indicates that one entity granted or established the noble title of baron or baroness for another entity.
-
C.
createdMarquess
Indicates that one entity formally established or granted the noble title of marquess to another entity.
-
D.
MountBattenTowerInstanceOf
Indicates that Mount Batten Tower is classified as an instance of a particular type or category.
-
E.
createdViscountIn
Indicates that an entity conferred or established the noble title of viscount in a particular place, context, or jurisdiction.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c71b688190b2e8ccfdf4db9037 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.