Triple
T34306267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Fort Beauséjour |
E880314
|
entity |
| Predicate | fortRenamedAs |
P173567
|
FINISHED |
| Object | Fort Cumberland |
—
|
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: Fort Cumberland | Statement: [Battle of Fort Beauséjour, fortRenamedAs, Fort Cumberland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fortRenamedAs Context triple: [Battle of Fort Beauséjour, fortRenamedAs, Fort Cumberland]
-
A.
wasRenamedIn
chosen
Indicates that an entity changed its name to a different one at or during a specific time or event.
-
B.
fortName
Indicates the name assigned to a specific fort or fortress structure.
-
C.
relocatedAndRenamed
Indicates that an entity has moved from one location to another and changed its name as part of that move.
-
D.
oftenRenamedAs
Indicates that an entity is frequently given a different name or title, reflecting common renaming or rebranding over time or across contexts.
-
E.
renamedDueTo
Indicates that one entity was renamed as a consequence of another specified cause, event, or condition.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:57 a.m.