Triple
T1088684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MedStar Capitals Iceplex |
E24110
|
entity |
| Predicate | numberOfIceSheets |
P23348
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [MedStar Capitals Iceplex, numberOfIceSheets, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIceSheets Context triple: [MedStar Capitals Iceplex, numberOfIceSheets, 2]
-
A.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
-
B.
hasSeaIce
Indicates that one entity possesses, contains, or is covered by sea ice in relation to another context or location.
-
C.
isLargestGlacierOn
Indicates that one glacier is the largest glacier located on a specified geographic entity (such as an island, continent, or region).
-
D.
notableGlacier
Indicates that the subject is a glacier recognized for its particular significance, prominence, or noteworthiness.
-
E.
seaIceType
Indicates the specific classification or category of sea ice associated with an entity (e.g., by age, thickness, or formation characteristics).
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97d85708190a1630256648aa4a2 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:42 p.m.