Triple
T1626901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellagio |
E35165
|
entity |
| Predicate | hasPositionOnLake |
P1489
|
FINISHED |
| Object | intersection of Lake Como’s three branches |
—
|
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: intersection of Lake Como’s three branches | Statement: [Bellagio, hasPositionOnLake, intersection of Lake Como’s three branches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPositionOnLake Context triple: [Bellagio, hasPositionOnLake, intersection of Lake Como’s three branches]
-
A.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
hasLagoon
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
-
C.
locatedOnWaterbody
chosen
Indicates that an entity is situated on or directly adjacent to a specified body of water.
-
D.
usesLakeFor
Indicates that an entity utilizes a lake as a resource or setting for some purpose, activity, or function.
-
E.
hasPositionOn
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to another entity.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.