Triple
T8801264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Seymour Hoffman as Freddie Miles |
E209412
|
entity |
| Predicate | addsToneOf |
P49759
|
FINISHED |
| Object | tension |
—
|
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: tension | Statement: [Philip Seymour Hoffman as Freddie Miles, addsToneOf, tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsToneOf Context triple: [Philip Seymour Hoffman as Freddie Miles, addsToneOf, tension]
-
A.
contributesToTone
chosen
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
B.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
C.
marksTones
Indicates that one entity applies or denotes tonal markings or distinctions on another entity, such as in language or notation.
-
D.
tonal
Indicates that one entity has a tone, pitch pattern, or tonal quality in relation to another (such as a language, sound, or musical element).
-
E.
hasEndingTone
Indicates that something concludes with a particular tone, mood, or intonational quality.
- 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_69ca836320e48190b5cf585b90a322c4 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb9c5c88190881b069e1face10c |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:44 p.m.