Triple
T14285205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mat |
E354151
|
entity |
| Predicate | oftenGivenAs |
P87213
|
FINISHED |
| Object | informal form of legal name Matthew |
—
|
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: informal form of legal name Matthew | Statement: [Mat, oftenGivenAs, informal form of legal name Matthew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenGivenAs Context triple: [Mat, oftenGivenAs, informal form of legal name Matthew]
-
A.
oftenExpressedAs
chosen
Indicates that one thing is frequently represented, stated, or manifested in the form of another.
-
B.
oftenSays
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
-
C.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
D.
oftenHeldToBe
Indicates that something is frequently regarded, considered, or believed to be a certain way by many people or in many contexts.
-
E.
isFrequentlyDescribedAs
Indicates that something is often characterized or referred to using a particular description or set of attributes.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697ef40c8190bea37724b28c2e99 |
completed | April 14, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.