Triple
T14892323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Anatomy Lesson |
E359781
|
entity |
| Predicate | hasAlterEgoCharacter |
P86336
|
FINISHED |
| Object | Nathan Zuckerman as Philip Roth’s alter ego |
—
|
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: Nathan Zuckerman as Philip Roth’s alter ego | Statement: [The Anatomy Lesson, hasAlterEgoCharacter, Nathan Zuckerman as Philip Roth’s alter ego]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlterEgoCharacter Context triple: [The Anatomy Lesson, hasAlterEgoCharacter, Nathan Zuckerman as Philip Roth’s alter ego]
-
A.
hasFictionalAlterEgoOf
chosen
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
B.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
C.
hasFictionalAlias
Indicates that an entity is known by an alternative name or identity within a fictional context.
-
D.
hasAlterEgoDevice
Indicates that an entity possesses or is associated with a device specifically used to enable, support, or manifest its alter ego.
-
E.
hasRapAlterEgoOf
Indicates that one entity is the rap-stage persona or alter ego used by another entity.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f883288190af602633fa7d6860 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:10 a.m.