Triple
T1524916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ennio Morricone |
E32312
|
entity |
| Predicate | numberOfTelevisionScores |
P30145
|
FINISHED |
| Object | over 100 |
—
|
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: over 100 | Statement: [Ennio Morricone, numberOfTelevisionScores, over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTelevisionScores Context triple: [Ennio Morricone, numberOfTelevisionScores, over 100]
-
A.
USNielsenRating
Indicates the television audience rating assigned to a program in the United States according to the Nielsen measurement system.
-
B.
mediaSignal
Indicates that one entity serves as a medium or channel through which a signal, message, or information is transmitted from a source to a receiver.
-
C.
televisionExposureLevel
Indicates the degree or amount of exposure an entity has to television content.
-
D.
broadcastRatingUS
Indicates the television content rating assigned to a broadcast in the United States.
-
E.
televisionAspect
Indicates the aspect ratio or format characteristics of a television display in relation to its width and height proportions.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a93d462f208190b27ef5cd631bce12 |
completed | March 5, 2026, 8:22 a.m. |
Created at: March 4, 2026, 7:26 p.m.