Triple
T17767533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haddie Braverman |
E443546
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Haddie |
—
|
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: Haddie | Statement: [Haddie Braverman, givenName, Haddie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haddie Context triple: [Haddie Braverman, givenName, Haddie]
-
A.
Maidie
Maidie is the central character of the television series "Dads," around whom the show's primary storylines and character dynamics revolve.
-
B.
Bettey
Bettey is a given name, likely a variant spelling of the name Betty.
-
C.
Arletta
Arletta, better known as Herleva of Falaise, was the mother of William the Conqueror and a notable figure in 11th-century Norman history.
-
D.
Molly Ockett
Molly Ockett was a well-known Abenaki healer and folk figure from the 18th–19th century New England region, remembered for her medical skills, generosity, and close relationships with local settlers.
-
E.
Hassie
chosen
Hassie is a given name, often used as a feminine first name in English-speaking countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485fccb9881908923564bf319f3c1 |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 10:11 a.m.