Triple
T21302383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Pearson |
E525101
|
entity |
| Predicate | hasDaughter |
P24357
|
FINISHED |
| Object | Tess Pearson |
—
|
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: Tess Pearson | Statement: [Beth Pearson, hasDaughter, Tess Pearson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tess Pearson Context triple: [Beth Pearson, hasDaughter, Tess Pearson]
-
A.
Tess Pearson
chosen
Tess Pearson is a fictional character from the television drama "This Is Us," known as the eldest daughter of Randall and Beth Pearson.
-
B.
Tess Carlisle
Tess Carlisle is the wealthy, strong-willed widow of a U.S. senator whose contentious relationship with her Secret Service detail drives the plot of the film "Guarding Tess."
-
C.
Tess McGill
Tess McGill is the ambitious, street-smart Staten Island secretary who fights to advance her career in the 1988 film "Working Girl."
-
D.
Tess Harper
Tess Harper is an American actress known for her work in film and television, including acclaimed roles in projects like "Crimes of the Heart" and "Tender Mercies."
-
E.
Tess Harding
Tess Harding is the sophisticated, career-driven political columnist portrayed by Katharine Hepburn in the 1942 film "Woman of the Year."
- 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385cd6308190bf300494833b048f |
completed | April 21, 2026, 8:42 a.m. |
Created at: April 16, 2026, 4:05 p.m.