Triple
T31703192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Old Man |
E809111
|
entity |
| Predicate | appearsInActStructure |
P34106
|
FINISHED |
| Object | throughout the play |
—
|
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: throughout the play | Statement: [The Old Man, appearsInActStructure, throughout the play]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInActStructure Context triple: [The Old Man, appearsInActStructure, throughout the play]
-
A.
actStructure
chosen
Indicates a structural or organizational relationship that defines how an action or activity is arranged, composed, or internally organized.
-
B.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
C.
appearsFor
Indicates that one entity is presented, shown, or made visible on behalf of, or in representation of, another entity.
-
D.
appearsWithActor
Indicates that one entity appears together on screen or in a scene with a specified actor.
-
E.
appearsInScriptType
Indicates that an entity is featured or occurs within a script of a specified type or category.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 30, 2026, 11:12 p.m.