Triple
T9313237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K-root |
E224054
|
entity |
| Predicate | hasPhysicalInstanceCount |
P17874
|
FINISHED |
| Object | many anycast sites worldwide |
—
|
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: many anycast sites worldwide | Statement: [K-root, hasPhysicalInstanceCount, many anycast sites worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalInstanceCount Context triple: [K-root, hasPhysicalInstanceCount, many anycast sites worldwide]
-
A.
numberOfInstances
chosen
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
B.
hasNumberOfLogicalServers
Indicates the quantity of logical servers associated with or contained within a given entity.
-
C.
hasPhysicalInterface
Indicates that one entity provides or includes a tangible, hardware-based connection point or medium through which another entity can physically interact or communicate.
-
D.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
E.
operatesOnPhysicalSystem
Indicates that an agent or process performs actions that affect or manipulate a physical system.
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd20b048a081909fd7ec0b6b863063 |
completed | April 1, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:37 p.m.