Triple
T1911969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becky |
E38129
|
entity |
| Predicate | hasColloquialUse |
P6990
|
FINISHED |
| Object | nickname |
—
|
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: nickname | Statement: [Becky, hasColloquialUse, nickname]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColloquialUse Context triple: [Becky, hasColloquialUse, nickname]
-
A.
hasColloquialVariety
Indicates that one linguistic form, expression, or variety is an informal, colloquial counterpart or version of another.
-
B.
isColloquialTerm
chosen
Indicates that one term is an informal or non-standard, colloquial way of referring to another term or concept.
-
C.
usesColloquialCharacters
Indicates that an expression, name, or text is written using informal, non-standard, or colloquial characters rather than formal or standard script.
-
D.
usedInSpokenForm
Indicates that something (such as a word, name, or expression) is employed in spoken language or oral communication.
-
E.
usedInformallyAlongside
Indicates that something is employed in an informal, non-standard way together with or in addition to something else.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafeba3d88190afcce67483d8625b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.