Triple
T5131973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Disappointment |
E115721
|
entity |
| Predicate | wasNamedInYear |
P62797
|
FINISHED |
| Object | 1788 |
—
|
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: 1788 | Statement: [Cape Disappointment, wasNamedInYear, 1788]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasNamedInYear Context triple: [Cape Disappointment, wasNamedInYear, 1788]
-
A.
playedInYear
Indicates that an entity participated in or was active in a particular activity, event, or role during a specified calendar year.
-
B.
castInYear
Indicates that an entity was cast in a role or production that took place in a specified year.
-
C.
formedInYear
Indicates the year in which an entity was originally established, created, or came into existence.
-
D.
usedNameToYear
Indicates that a particular name was in use or valid during a specified year.
-
E.
associatedWithYearFilm
Indicates a relationship where something (such as an event, award, or record) is linked to or pertains to a specific film released or identified in a given year.
- F. None of above. chosen
Provenance (4 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7fee42748190967013828973cce0 |
completed | March 20, 2026, 5:12 p.m. |
Created at: March 20, 2026, 1:42 p.m.