Triple
T28617578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Virtual Server |
E724306
|
entity |
| Predicate | acquiredTechnologyFrom |
P167920
|
FINISHED |
| Object | Connectix |
—
|
NE NERFINISHED |
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: Connectix | Statement: [Microsoft Virtual Server, acquiredTechnologyFrom, Connectix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acquiredTechnologyFrom Context triple: [Microsoft Virtual Server, acquiredTechnologyFrom, Connectix]
-
A.
acquiredFor
Indicates that one entity obtained or purchased another entity specifically for the benefit, use, or purpose of a third entity.
-
B.
acquiredWith
Indicates that one entity was obtained, purchased, or gained together with or by means of another entity.
-
C.
couldBeAcquiredBy
Indicates that one entity is a potential target to be obtained, bought, or taken over by another entity.
-
D.
acquisitionResultedIn
Indicates that an acquisition event led to a particular outcome, state, or consequence for the involved entities.
-
E.
acquisitionCategory
Indicates the type or classification of an acquisition associated with an entity or transaction.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 4:32 a.m.