Triple
T27075181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 15 Park Avenue |
E685440
|
entity |
| Predicate | portraysCharacterWithCondition |
P181303
|
FINISHED |
| Object | schizophrenia |
—
|
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: schizophrenia | Statement: [15 Park Avenue, portraysCharacterWithCondition, schizophrenia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysCharacterWithCondition Context triple: [15 Park Avenue, portraysCharacterWithCondition, schizophrenia]
-
A.
portraysMainCharacter
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
-
B.
portrayedByCharacterType
Indicates that an entity is depicted or represented by a character of a specified type (e.g., hero, villain, sidekick) in a narrative or media work.
-
C.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
D.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
-
E.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
| PDg | Predicate description generation | batch_69f7688cea58819098bdfd7c80df7634 |
completed | May 3, 2026, 3:23 p.m. |
Created at: April 27, 2026, 8:30 a.m.