Triple
T528507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AOL Instant Messenger |
E10976
|
entity |
| Predicate | userInterfaceLanguage |
P4149
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [AOL Instant Messenger, userInterfaceLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: userInterfaceLanguage Context triple: [AOL Instant Messenger, userInterfaceLanguage, English]
-
A.
languageOfInterface
chosen
Indicates the language used by or presented in a user interface.
-
B.
userInterface
Indicates a relationship where one entity serves as the interface or interaction layer through which a user engages with another system, service, or resource.
-
C.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
D.
identityLanguage
Indicates that two language entities are identical or represent the same language.
-
E.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d39b4c81909f265b3501b5ec1d |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f01ac3ec8190a94a05955532c7fa |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.