Triple
T34937362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pretty Mouth and Green My Eyes |
E1007613
|
entity |
| Predicate | primaryTime |
P197694
|
FINISHED |
| Object | late night |
—
|
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: late night | Statement: [Pretty Mouth and Green My Eyes, primaryTime, late night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTime Context triple: [Pretty Mouth and Green My Eyes, primaryTime, late night]
-
A.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
B.
primarySingle
Indicates that an entity has exactly one main or primary association of the specified type, with no additional concurrent primary associations.
-
C.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
D.
primaryBroadcastTime
chosen
Indicates the main or scheduled time at which a broadcast (such as a TV or radio program) is first aired.
-
E.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.