Triple
T34755749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Washington McLintock |
E1001915
|
entity |
| Predicate | hasDaughterInFiction |
P114951
|
FINISHED |
| Object | Becky McLintock |
—
|
NE NERFINISHED |
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: Becky McLintock | Statement: [George Washington McLintock, hasDaughterInFiction, Becky McLintock]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDaughterInFiction Context triple: [George Washington McLintock, hasDaughterInFiction, Becky McLintock]
-
A.
hasChildInFiction
Indicates that a fictional work or character includes another character as their child within the fictional narrative.
-
B.
fictionalDaughter
chosen
Indicates that one entity is the daughter of another within a fictional or narrative context.
-
C.
hasFictionalSibling
Indicates that one entity is a fictional character who is a sibling of another entity.
-
D.
isHeiressInFiction
Indicates that a character is portrayed as an heiress within a fictional work or narrative.
-
E.
hasNotableDaughter
Indicates that an entity has at least one daughter who is notable or significant in some recognized way.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.