Triple
T974823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Morning America |
E21027
|
entity |
| Predicate | formatCharacteristic |
P130
|
FINISHED |
| Object | anchor-led program |
—
|
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: anchor-led program | Statement: [Good Morning America, formatCharacteristic, anchor-led program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formatCharacteristic Context triple: [Good Morning America, formatCharacteristic, anchor-led program]
-
A.
format
chosen
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
B.
transportCharacteristic
Indicates a relationship where a specific characteristic, property, or feature is attributed to a mode or instance of transport.
-
C.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
E.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b460a5c0819087b03dfb8a3af2c2 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.