Triple
T27053374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Datapoint 2200 |
E684837
|
entity |
| Predicate | mainUseCase |
P161803
|
FINISHED |
| Object | data entry |
—
|
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: data entry | Statement: [Datapoint 2200, mainUseCase, data entry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainUseCase Context triple: [Datapoint 2200, mainUseCase, data entry]
-
A.
mainCase
Indicates that one case is the primary or central case associated with an entity or context, distinguishing it from other related cases.
-
B.
mainFunctions
Indicates that the subject serves as the primary or central functional component or role for the object.
-
C.
mainUseContinued
Indicates that the primary use or function of something persists or remains in effect over a subsequent period.
-
D.
mainSingle
Indicates that an entity is the primary or sole main instance among a set of related entities.
-
E.
mainPresenter
Indicates that one entity serves as the primary or lead presenter for another entity, such as an event, program, or presentation.
- 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622b145848190b67cfdc47da6a887 |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 8:15 a.m.