Triple
T15911711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America: A Patriotic Primer |
E385863
|
entity |
| Predicate | alphabetLetterCount |
P3567
|
FINISHED |
| Object | 26 |
—
|
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: 26 | Statement: [America: A Patriotic Primer, alphabetLetterCount, 26]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alphabetLetterCount Context triple: [America: A Patriotic Primer, alphabetLetterCount, 26]
-
A.
alphabet
Indicates that one entity is an alphabet or set of symbols used for representing elements (such as characters or tokens) in relation to another entity.
-
B.
hasLetterCount
chosen
Indicates that an entity is associated with a specific number representing how many letters it contains.
-
C.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
D.
alphabetRange
Indicates that one entity specifies a contiguous range of letters in an alphabet that extends from the starting letter to the ending letter.
-
E.
hasNumberOfLetters
Indicates a relationship where an entity is associated with the count of letters it contains.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.