Triple
T13874889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Wendell |
E333554
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wendell |
E148262
|
NE 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: Wendell | Statement: [Elizabeth Wendell, familyName, Wendell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendell Context triple: [Elizabeth Wendell, familyName, Wendell]
-
A.
Wendell
chosen
Wendell is a masculine given name of English origin that gained prominence in the United States, notably borne by figures such as abolitionist orator Wendell Phillips.
-
B.
Wardell
Wardell is the given first name of American character actor Ward Bond, known for his prolific roles in classic Hollywood films and Westerns.
-
C.
Weldon
Weldon is the middle name of James Weldon Johnson, the influential African American writer, civil rights activist, and leader of the NAACP.
-
D.
Weldon
Weldon is a small unincorporated community in California’s Kern County, situated in the rural Kern River Valley region.
-
E.
Verdell
Verdell is the small Brussels Griffon dog from the film "As Good as It Gets," known for softening the misanthropic character Melvin Udall.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be4031c8190bef5865ec23b18a0 |
completed | April 14, 2026, 9:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c109ac5c819090b2b7e43334f904 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.