Triple
T511453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Carnegie |
E10616
|
entity |
| Predicate | hasShoreLength |
P1568
|
FINISHED |
| Object | approximately 7 miles |
—
|
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: approximately 7 miles | Statement: [Lake Carnegie, hasShoreLength, approximately 7 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoreLength Context triple: [Lake Carnegie, hasShoreLength, approximately 7 miles]
-
A.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
B.
shorelineLength
chosen
Indicates the total measured extent of a land area’s boundary where it meets a body of water.
-
C.
hasSeaAccess
Indicates that an entity has direct access to the sea, typically via a coastline, port, or navigable waterway connected to the sea.
-
D.
hasSeaCondition
Indicates that an entity is associated with or characterized by a particular state or condition of the sea.
-
E.
hasCityOnShore
Indicates that a city is located on or directly adjacent to the shore of a body of water.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f16768c081909d05537ff070868b |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edff001c81909182a7e26c6dc51b |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.