Triple
T7881139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Prismatic Spring |
E182980
|
entity |
| Predicate | rankBySizeInUS |
P31652
|
FINISHED |
| Object | largest hot spring in the United States |
—
|
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: largest hot spring in the United States | Statement: [Grand Prismatic Spring, rankBySizeInUS, largest hot spring in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankBySizeInUS Context triple: [Grand Prismatic Spring, rankBySizeInUS, largest hot spring in the United States]
-
A.
rankByCapacityInUS
Indicates the relative ordering of entities based on their capacity within the United States.
-
B.
rankingInCountryBySize
chosen
Indicates the position of an entity in an ordered list of entities within a specific country, based on their relative size.
-
C.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
-
D.
regionRankBySize
Indicates the relative ordering of regions based on their physical size, from largest to smallest (or vice versa).
-
E.
rankByPopulationInUS
Indicates the relative ordering of entities based on the size of their populations within the United States.
- 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_69ca828af6e48190a06ee7010d8f0e64 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bffbc481908e868ab98a38e10a |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:58 p.m.