Triple
T5493179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detroit Seamount |
E123749
|
entity |
| Predicate | hasLargeVolume |
P64433
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Detroit Seamount, hasLargeVolume, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargeVolume Context triple: [Detroit Seamount, hasLargeVolume, true]
-
A.
hasLargeScale
Indicates that an entity operates, exists, or is implemented at a large or extensive scale relative to typical or baseline cases.
-
B.
hasLargePresenceIn
Indicates that an entity maintains a significant or dominant level of activity, influence, or representation within a specified location, domain, or context.
-
C.
capacityCategory
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
-
D.
hasHigh
Indicates that an entity possesses a high level, degree, or intensity of a specified attribute or property.
-
E.
storageCapacity
Indicates the maximum amount of data or material that a storage entity can hold.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9281a0148190bb7a8dae9c991b9c |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a8df6481908d1643f7342fe6f0 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd925c62a88190ac932444d5170bdd |
completed | March 20, 2026, 6:30 p.m. |
Created at: March 20, 2026, 2:10 p.m.