Triple
T15731836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawaiian hotspot |
E381363
|
entity |
| Predicate | hotspotTrackLength |
P119971
|
FINISHED |
| Object | over 6000 kilometers |
—
|
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: over 6000 kilometers | Statement: [Hawaiian hotspot, hotspotTrackLength, over 6000 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hotspotTrackLength Context triple: [Hawaiian hotspot, hotspotTrackLength, over 6000 kilometers]
-
A.
hotspot
Indicates that a location or entity is a focal point of intense activity, interest, or occurrence relative to others.
-
B.
isHotspotTrackOf
Indicates that one entity is a hotspot track that corresponds to, or is derived from, another entity.
-
C.
hotspotType
Indicates the specific category or kind of hotspot associated with an entity or location.
-
D.
mainTrackDistance
Indicates the distance measured along the primary or main track between two referenced points or entities.
-
E.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd3614481908b2694b1d3550058 |
completed | April 16, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0094af5b481908ad51d5d7ba0c726 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 4:46 a.m.