Triple
T35828022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Pentangeli |
E1035705
|
entity |
| Predicate | resentfulOf |
P93812
|
FINISHED |
| Object | Michael Corleone’s leadership style |
—
|
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: Michael Corleone’s leadership style | Statement: [Frank Pentangeli, resentfulOf, Michael Corleone’s leadership style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resentfulOf Context triple: [Frank Pentangeli, resentfulOf, Michael Corleone’s leadership style]
-
A.
isEmbittered
Indicates that an entity harbors persistent bitterness or resentment, typically as a result of past experiences or perceived wrongs.
-
B.
harborsResentmentToward
chosen
Indicates that one entity holds ongoing bitterness, anger, or ill will directed at another entity.
-
C.
upset
Indicates that one entity causes another to feel distressed, unhappy, or emotionally disturbed.
-
D.
hasVengefulTone
Indicates that the subject expresses anger, resentment, or a desire for revenge toward another entity in its tone or manner.
-
E.
belligerentAgainst
Indicates a hostile or aggressive stance, conflict, or antagonistic behavior directed by one entity against another.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.