Triple
T12814770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take Good Care of My Baby |
E306361
|
entity |
| Predicate | hasSubjectPronoun |
P37239
|
FINISHED |
| Object | first-person narrator |
—
|
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: first-person narrator | Statement: [Take Good Care of My Baby, hasSubjectPronoun, first-person narrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectPronoun Context triple: [Take Good Care of My Baby, hasSubjectPronoun, first-person narrator]
-
A.
hasSubjectPronouns
chosen
Indicates that an entity is associated with one or more pronouns that function as its grammatical subject in sentences.
-
B.
hasSubjectPosition
Indicates that an entity occupies or is assigned to a particular subject role or position within a structure, context, or organization.
-
C.
hasPronounForIt
Indicates that one entity serves as the pronoun form referring to another entity.
-
D.
hasAnaphora
Indicates that one expression in a text refers back to another earlier expression for its interpretation.
-
E.
hasPronounForYouSingular
Indicates that there is a pronoun form specifically used to address a single person as "you" in the given language or context.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9beb30819097c256a5aab9a4c8 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.