Triple
T3632826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holden Caulfield |
E76995
|
entity |
| Predicate | fantasy |
P49698
|
FINISHED |
| Object | being the catcher in the rye |
—
|
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: being the catcher in the rye | Statement: [Holden Caulfield, fantasy, being the catcher in the rye]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fantasy Context triple: [Holden Caulfield, fantasy, being the catcher in the rye]
-
A.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
fate
Indicates that an entity is destined or predetermined to experience a particular outcome or course of events beyond its control.
-
C.
typeOfMagic
Indicates that one entity is a specific category, school, or kind of magic associated with another entity.
-
D.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
E.
fictionalAge
Indicates the age attributed to an entity within a fictional or narrative context, rather than its real-world age.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30457608190840fb5b33f9965c4 |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb842be7c8190b7dfdb7c906f294c |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:23 p.m.