Triple
T15612927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hemkunt Sahib |
E375342
|
entity |
| Predicate | shapeOfLake |
P18842
|
FINISHED |
| Object | roughly star-shaped |
—
|
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: roughly star-shaped | Statement: [Hemkunt Sahib, shapeOfLake, roughly star-shaped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shapeOfLake Context triple: [Hemkunt Sahib, shapeOfLake, roughly star-shaped]
-
A.
lakeShape
chosen
Indicates the geometric or physical outline/form that a lake possesses.
-
B.
lakeDiameter
Indicates the measured straight-line distance across a lake, typically through its center, representing the lake’s diameter.
-
C.
mouthLake
Indicates the location where a river or stream flows into and forms part of a lake.
-
D.
isLakeType
Indicates that one entity is a specific type or category of lake in relation to another entity.
-
E.
maximumLake
Indicates that the subject entity is the lake with the greatest value (such as size, volume, or another specified measure) among a given set of 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8148a0819087d6d69cc84487ca |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.