Triple
T2002408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Root Server System |
E43499
|
entity |
| Predicate | hasNumberOfLogicalServers |
P35056
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Root Server System, hasNumberOfLogicalServers, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfLogicalServers Context triple: [Root Server System, hasNumberOfLogicalServers, 13]
-
A.
numberOfHosts
Indicates the total count of distinct hosts associated with or involved in a given entity or event.
-
B.
hasServer
Indicates that one entity functions as or possesses a server that provides services or resources to another entity.
-
C.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
D.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
E.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8820cec8190a945e5daeb8c9df6 |
completed | March 7, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.