Triple
T29193820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Am Charlotte Simmons |
E740066
|
entity |
| Predicate | hasFictionalUniversity |
P146006
|
FINISHED |
| Object | Dupont University |
—
|
NE NERFINISHED |
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: Dupont University | Statement: [I Am Charlotte Simmons, hasFictionalUniversity, Dupont University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalUniversity Context triple: [I Am Charlotte Simmons, hasFictionalUniversity, Dupont University]
-
A.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
B.
fictionalUniversityAffiliation
chosen
Indicates that an entity is affiliated with a university that exists only in a fictional or imaginary context.
-
C.
setInFictionalUniversity
Indicates that the events or narrative take place within the setting of a fictional university.
-
D.
hasUniversities
Indicates that an entity possesses, contains, or is associated with one or more universities.
-
E.
isUrbanUniversity
Indicates that a university is located in, or primarily associated with, an urban (city) environment.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: April 28, 2026, 12:03 p.m.