Triple
T7024017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam Bryant |
E162897
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Pamela |
E328551
|
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: Pamela | Statement: [Pam Bryant, givenName, Pamela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pamela Context triple: [Pam Bryant, givenName, Pamela]
-
A.
Pamela
chosen
Pamela is the given name of Pam Grier, the pioneering American actress celebrated for her iconic roles in 1970s blaxploitation films and later works like "Jackie Brown."
-
B.
Pamela, a Love Story
"Pamela, a Love Story" is a 2023 Netflix documentary film that offers an intimate, first-person look at Pamela Anderson’s life, career, and public image.
-
C.
Clarissa
Clarissa is the given first name of Clara Barton, the pioneering American nurse and founder of the American Red Cross.
-
D.
Evelina
Evelina is an epistolary novel by Frances Burney that follows a young woman's social and romantic adventures in 18th-century English society.
-
E.
The Governess
The Governess is an 18th-century genre painting by French artist Jean-Baptiste-Siméon Chardin that depicts a domestic scene emphasizing quiet moral instruction and middle-class family life.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1fa043c81909c900e394a5972f9 |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c77581e2a88190ad2ec9855772c6a5 |
completed | March 28, 2026, 6:30 a.m. |
Created at: March 27, 2026, 2:35 p.m.