Triple
T14334660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | highly composite number |
E355438
|
entity |
| Predicate | yearCharacterized |
P13770
|
FINISHED |
| Object | 1915 |
—
|
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: 1915 | Statement: [highly composite number, yearCharacterized, 1915]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearCharacterized Context triple: [highly composite number, yearCharacterized, 1915]
-
A.
reignCharacterizedBy
Indicates that a ruler’s period of governance is defined or distinguished by a particular quality, condition, or notable feature.
-
B.
yearDescribed
Indicates the year in which something (typically a species, object, or concept) was formally described or documented.
-
C.
yearDescribedAs
chosen
Indicates the specific year in which something was formally characterized, documented, or described.
-
D.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
yearDepicted
Indicates the specific year in which the subject is portrayed, represented, or set.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c20d2148190bb534bef338e871d |
completed | April 14, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:13 a.m.