Triple
T16034935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curley’s wife |
E388947
|
entity |
| Predicate | isUnnamedInWork |
P111602
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Curley’s wife, isUnnamedInWork, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUnnamedInWork Context triple: [Curley’s wife, isUnnamedInWork, true]
-
A.
isUnnamedBeyondDescription
Indicates that something lacks a specific name and can only be referred to or characterized in vague, indescribable, or ineffable terms.
-
B.
namedForWork
Indicates that one entity is named in honor of, or derived from the title of, a particular work (such as a book, film, artwork, or other creative production).
-
C.
namedForWorkOn
Indicates that an entity is named in honor of another entity specifically because of that entity’s work or contributions in a particular field or endeavor.
-
D.
nicknameOfContainedWork
Indicates that a name is a nickname or informal title used for a work that is contained within another larger work.
-
E.
oftenUnnamedIn
chosen
Indicates that an entity frequently appears in a given context, work, or setting without being explicitly named.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.