Triple
T12674648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All This, and Heaven Too |
E302773
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jeffrey Lynn |
E391237
|
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: Jeffrey Lynn | Statement: [All This, and Heaven Too, starring, Jeffrey Lynn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Lynn Context triple: [All This, and Heaven Too, starring, Jeffrey Lynn]
-
A.
Jeffrey Lynn
chosen
Jeffrey Lynn was an American film and stage actor best known for his roles in 1930s and 1940s Hollywood dramas and romances.
-
B.
Jeffrey Byron
Jeffrey Byron is an American actor known for his work in film and television since the 1960s, including roles in genre and action productions.
-
C.
Jeffrey Heath
Jeffrey Heath is a linguist renowned for his extensive fieldwork and documentation of Dogon and other African languages.
-
D.
Jeffrey Hayden
Jeffrey Hayden was an American television and film director known for his extensive work in mid-20th-century TV dramas and variety shows.
-
E.
Jeffrey Lynn Green
Jeffrey Lynn Green is an American former professional basketball player and current NBA forward known for his versatility and long career with multiple teams.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961af991c8190b6079cb57e593b8f |
completed | April 10, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ac916748190821c0cdabe54fcbc |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 5:20 p.m.