Triple
T34958203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fury |
E1008174
|
entity |
| Predicate | portraysKesAs |
P100368
|
FINISHED |
| Object | older and embittered |
—
|
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: older and embittered | Statement: [Fury, portraysKesAs, older and embittered]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysKesAs Context triple: [Fury, portraysKesAs, older and embittered]
-
A.
portraysPersonAs
chosen
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
B.
portraysCharacterIn
Indicates that one entity depicts or represents a particular character within a work, such as a film, show, or other narrative medium.
-
C.
portraysMainCharacter
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
-
D.
portraysRoleTrait
Indicates that one entity depicts or represents a particular role or character trait of another entity.
-
E.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
Created at: May 3, 2026, 4 p.m.