Triple
T9394630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Orlean |
E226111
|
entity |
| Predicate | hasWrittenFor |
P11775
|
FINISHED |
| Object | Esquire |
E85384
|
NE 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: Esquire | Statement: [Susan Orlean, hasWrittenFor, Esquire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esquire Context triple: [Susan Orlean, hasWrittenFor, Esquire]
-
A.
Esquire
Esquire is a courtesy title traditionally used in English-speaking countries to denote a man of higher social rank or, in modern usage, a practicing lawyer in the United States.
-
B.
Esquire magazine
chosen
Esquire magazine is a long-running American men’s magazine known for its literary journalism, in-depth reporting, and stylish coverage of culture, politics, and fashion.
-
C.
Men's Journal
Men's Journal is an American lifestyle magazine focused on adventure, travel, fitness, gear, and men's interests.
-
D.
GQ
GQ is a leading international men's magazine known for its coverage of fashion, culture, and style.
-
E.
GQ
GQ is the two-letter ISO 3166-1 alpha-2 country code for Equatorial Guinea, a Central African nation on the Atlantic coast.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd511150008190be04142e477e8bf1 |
completed | April 1, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1010ffcd4819088edafbdb43c2c00 |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:45 p.m.