Triple
T7985817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apache ZooKeeper |
E185678
|
entity |
| Predicate | recommendedServerCount |
P80187
|
FINISHED |
| Object | odd number of servers |
—
|
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: odd number of servers | Statement: [Apache ZooKeeper, recommendedServerCount, odd number of servers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedServerCount Context triple: [Apache ZooKeeper, recommendedServerCount, odd number of servers]
-
A.
maximumSlotsRecommended
Indicates the highest number of slots that is advised or suggested to be used in a given context.
-
B.
numberOfHosts
Indicates the total count of distinct hosts associated with or involved in a given entity or event.
-
C.
numberOfRecommendations
Indicates the quantity of recommendations associated with or given to a particular entity or item.
-
D.
typicalServer
Indicates that an entity functions as a standard or representative example of a server within a given context or system.
-
E.
recommendedSpeed
Indicates the speed that is advised or suggested as appropriate under given conditions, rather than required or actual speed.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c4b87e48190a797f5363c8f0a04 |
completed | March 31, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69cb048009a08190b4c577208a9f8f76 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:15 p.m.