Triple
T32062437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MPEG-4 SAOL |
E818778
|
entity |
| Predicate | hasTextualSyntax |
P192925
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [MPEG-4 SAOL, hasTextualSyntax, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextualSyntax Context triple: [MPEG-4 SAOL, hasTextualSyntax, yes]
-
A.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
B.
hasTextualBase
Indicates that one entity serves as the underlying textual source or foundation upon which another entity is based or derived.
-
C.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
D.
hasTextualCorpus
Indicates that an entity is associated with or possesses a collection of written or textual materials.
-
E.
hasTextParser
Indicates that an entity is associated with or utilizes a specific text parser to analyze or process textual data.
- 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_69f348fdacec8190b9f74375ca3b2094 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69fd328298ac8190b6bd5ded7dca270d |
completed | May 8, 2026, 12:46 a.m. |
Created at: May 1, 2026, 12:22 a.m.