Triple
T122416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIG |
E2477
|
entity |
| Predicate | usedInContextOf |
P2919
|
FINISHED |
| Object | computing research |
—
|
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: computing research | Statement: [SIG, usedInContextOf, computing research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInContextOf Context triple: [SIG, usedInContextOf, computing research]
-
A.
contextOf
chosen
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
- F. None of above.
Provenance (3 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a2573b4e7481909ee09d2899f8a74b |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564928208190966a619680a0d6e2 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.