Triple
T18204966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BigBird |
E435879
|
entity |
| Predicate | hasAttentionPattern |
P130222
|
FINISHED |
| Object | global attention |
—
|
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: global attention | Statement: [BigBird, hasAttentionPattern, global attention]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttentionPattern Context triple: [BigBird, hasAttentionPattern, global attention]
-
A.
hasBearingPattern
Indicates a relationship where an object or system exhibits or is characterized by a specific bearing arrangement or configuration pattern.
-
B.
hasUsePattern
Indicates a characteristic or recurring way in which something is typically used or applied.
-
C.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
D.
hasPlanningPattern
Indicates that an entity follows or is associated with a particular planning pattern or structured approach to planning.
-
E.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.