Triple
T27582860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Address Book |
E699624
|
entity |
| Predicate | replicatesBetween |
P162724
|
FINISHED |
| Object | Domino 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: Domino servers | Statement: [Public Address Book, replicatesBetween, Domino servers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replicatesBetween Context triple: [Public Address Book, replicatesBetween, Domino servers]
-
A.
replicatesDuring
Indicates that one entity undergoes replication during the time period, phase, or process specified by the other entity.
-
B.
repetitionOf
Indicates that one entity is a repeated occurrence or instance of another entity, preserving the same content or pattern.
-
C.
repetitionCount
Indicates the number of times a particular event, action, or pattern is repeated within a given context.
-
D.
usesRepetition
Indicates that one entity employs repeated elements, actions, or patterns as a deliberate feature or technique in relation to another entity or context.
-
E.
replicaOf
Indicates that one entity is an exact or near-exact copy of another entity, preserving its form, structure, or content.
- 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63017bbfc81908e0058e1b6afe3a1 |
completed | May 2, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d14c24c81909e86678c1b5fd429 |
completed | May 2, 2026, 4:57 p.m. |
Created at: April 27, 2026, 2:03 p.m.