Triple
T7045242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N. T. Rama Rao Jr. |
E163614
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Temper
Temper is a 2015 Telugu-language action drama film starring N. T. Rama Rao Jr. as a corrupt police officer whose life changes after a transformative incident.
|
E638832
|
NE FINISHED |
How this triple was built (4 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: Temper | Statement: [N. T. Rama Rao Jr., notableWork, Temper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temper Context triple: [N. T. Rama Rao Jr., notableWork, Temper]
-
A.
The Mood
"The Mood" is a track by Kid Cudi from his album *Man on the Moon II: The Legend of Mr. Rager*, known for its introspective lyrics and atmospheric production.
-
B.
Stimmung
Stimmung is a groundbreaking 1968 vocal composition by Karlheinz Stockhausen that explores overtone singing, extended vocal techniques, and meditative repetition.
-
C.
Tiepido
Tiepido is a small river in northern Italy that serves as a tributary of the Panaro River.
-
D.
Mood
Mood is an American hip hop group known for its underground, jazz-influenced sound and collaborations with producer Hi-Tek.
-
E.
Mood
"Mood" is a popular Afrobeats song by Nigerian artist Wizkid, known for its smooth, laid-back vibe and melodic delivery.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Temper Triple: [N. T. Rama Rao Jr., notableWork, Temper]
Generated description
Temper is a 2015 Telugu-language action drama film starring N. T. Rama Rao Jr. as a corrupt police officer whose life changes after a transformative incident.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Temper Target entity description: Temper is a 2015 Telugu-language action drama film starring N. T. Rama Rao Jr. as a corrupt police officer whose life changes after a transformative incident.
-
A.
The Mood
"The Mood" is a track by Kid Cudi from his album *Man on the Moon II: The Legend of Mr. Rager*, known for its introspective lyrics and atmospheric production.
-
B.
Stimmung
Stimmung is a groundbreaking 1968 vocal composition by Karlheinz Stockhausen that explores overtone singing, extended vocal techniques, and meditative repetition.
-
C.
Tiepido
Tiepido is a small river in northern Italy that serves as a tributary of the Panaro River.
-
D.
Mood
Mood is an American hip hop group known for its underground, jazz-influenced sound and collaborations with producer Hi-Tek.
-
E.
Mood
"Mood" is a popular Afrobeats song by Nigerian artist Wizkid, known for its smooth, laid-back vibe and melodic delivery.
- F. None of above. chosen
Provenance (5 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e238c7a4819095f5ff7283d48da8 |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7887799f48190b4fa311defd8e9fd |
completed | March 28, 2026, 7:51 a.m. |
| NEDg | Description generation | batch_69c7893f85588190b1ed983f00ea2532 |
completed | March 28, 2026, 7:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c78b0fe83481909cad77ce740b81d5 |
completed | March 28, 2026, 8:02 a.m. |
Created at: March 27, 2026, 2:37 p.m.