Triple
T4249994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susten Pass |
E95824
|
entity |
| Predicate | hasLookoutPoints |
P51936
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Susten Pass, hasLookoutPoints, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLookoutPoints Context triple: [Susten Pass, hasLookoutPoints, yes]
-
A.
hasLookout
Indicates that one entity serves as a lookout or watchful observer for another entity, monitoring for potential events, threats, or changes.
-
B.
hasNumberOfOverlooks
chosen
Indicates the specific count of overlooks (such as viewing points or vantage spots) associated with an entity.
-
C.
hasObservationArea
Indicates that an entity possesses or includes a designated area from which observations or monitoring activities are conducted.
-
D.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
E.
hasObservationSite
Indicates that something (such as a measurement, event, or observation activity) is associated with or took place at a specific observation site or location.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e9f11008190a0021e0ad730a79d |
completed | March 12, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.