Triple
T1746807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape St. Vincent |
E38352
|
entity |
| Predicate | cliffHeight |
P18448
|
FINISHED |
| Object | about 60 to 75 meters |
—
|
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: about 60 to 75 meters | Statement: [Cape St. Vincent, cliffHeight, about 60 to 75 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cliffHeight Context triple: [Cape St. Vincent, cliffHeight, about 60 to 75 meters]
-
A.
hasCliffHeight
chosen
Indicates the relationship between a cliff and the measurement of its vertical height.
-
B.
hasCliff
Indicates that something possesses or features a steep, high rock face or abrupt vertical drop as part of its structure or environment.
-
C.
hasCliffs
Indicates that something possesses or is characterized by the presence of cliffs.
-
D.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
E.
totalAscent
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.