Triple
T24157793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Webster, Massachusetts |
E598735
|
entity |
| Predicate | hasLakeAlsoKnownAs |
P137822
|
FINISHED |
| Object | Webster Lake |
—
|
NE NERFINISHED |
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: Webster Lake | Statement: [Webster, Massachusetts, hasLakeAlsoKnownAs, Webster Lake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeAlsoKnownAs Context triple: [Webster, Massachusetts, hasLakeAlsoKnownAs, Webster Lake]
-
A.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
B.
hasLakeName
Indicates that an entity (such as a lake or related feature) bears or is associated with a specific lake name.
-
C.
lakeAlternateName
chosen
Indicates that a lake is known by an alternative or additional name.
-
D.
mouthLake
Indicates the location where a river or stream flows into and forms part of a lake.
-
E.
hasLakes
Indicates that one entity possesses, contains, or is characterized by the presence of one or more lakes.
- 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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e6d9fc8190a296f4f2b6d0d5e1 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:31 p.m.