Triple
T21737351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ingram |
E536559
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Ingrams |
—
|
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: Ingrams | Statement: [Ingram, hasVariant, Ingrams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ingrams Context triple: [Ingram, hasVariant, Ingrams]
-
A.
Ingram
chosen
Ingram is a surname of English origin borne by various notable individuals across fields such as music, sports, and academia.
-
B.
Ingram
Ingram is a small city in Kerr County, Texas, known for its scenic Hill Country setting along the Guadalupe River.
-
C.
Robert Appleton Company
Robert Appleton Company was an early 20th-century New York-based publishing house best known for producing the original multi-volume Catholic Encyclopedia.
-
D.
Harcout
Harcourt is a small rural town in central Victoria, Australia, known historically for its apple orchards and granite quarries.
-
E.
Hulton Press
Hulton Press was a British magazine and newspaper publisher best known for producing the influential weekly comic "Eagle," which featured the iconic character Dan Dare.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd0d33dc81908a4a79abc33355d1 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 16, 2026, 6:49 p.m.