Triple
T11939126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Lumia 950 |
E284127
|
entity |
| Predicate | simCount |
P102254
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Microsoft Lumia 950, simCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: simCount Context triple: [Microsoft Lumia 950, simCount, 1]
-
A.
simType
Indicates that two entities share the same or a comparable type, category, or classification.
-
B.
registerCount
Indicates the number of registers associated with or allocated to a given entity in a system.
-
C.
count
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
signCount
Indicates the number of signs associated with, produced by, or present in relation to a given entity or context.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903415d2481909d84e6727454b9fe |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.