Triple
T35385656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Harmon |
E1022785
|
entity |
| Predicate | fullGivenName |
P161411
|
FINISHED |
| Object | Elizabeth Harmon |
—
|
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: Elizabeth Harmon | Statement: [Beth Harmon, fullGivenName, Elizabeth Harmon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fullGivenName Context triple: [Beth Harmon, fullGivenName, Elizabeth Harmon]
-
A.
fullGivenNameOf
chosen
Indicates that one entity is the complete, formal given name corresponding to another entity (such as a person or identifier).
-
B.
fullName
Indicates that an entity has a complete personal name, typically combining given name(s) and family name into a single string.
-
C.
givenName
Indicates the personal first name assigned to an individual.
-
D.
fullLegalName
Indicates that the associated value is the complete, official legal name of the entity as recognized by law or formal records.
-
E.
givenFirstAndMiddleNamesOf
Indicates that one entity has been provided with the first and middle names of another entity.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f50080819095ff3c2cefc74fea |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.