Triple
T7881140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Prismatic Spring |
E182980
|
entity |
| Predicate | rankBySizeInWorld |
P79538
|
FINISHED |
| Object | third-largest hot spring in the world |
—
|
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: third-largest hot spring in the world | Statement: [Grand Prismatic Spring, rankBySizeInWorld, third-largest hot spring in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankBySizeInWorld Context triple: [Grand Prismatic Spring, rankBySizeInWorld, third-largest hot spring in the world]
-
A.
rankingInCountryBySize
Indicates the position of an entity in an ordered list of entities within a specific country, based on their relative size.
-
B.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
C.
regionRankBySize
Indicates the relative ordering of regions based on their physical size, from largest to smallest (or vice versa).
-
D.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
E.
capacityRankInWorld
Indicates the relative position or ranking of an entity’s capacity compared to all similar entities worldwide.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:58 p.m.