Triple
T17924738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foster Hewitt |
E448161
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Foster |
—
|
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: Foster | Statement: [Foster Hewitt, givenName, Foster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Foster Context triple: [Foster Hewitt, givenName, Foster]
-
A.
Foster
chosen
Foster is a common English surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and academia.
-
B.
Foster
Foster is a small rural town in western Rhode Island known for its forests, historic character, and low population density.
-
C.
Foster Boy
Foster Boy is a legal drama film that follows a corporate lawyer forced to confront corruption and abuse within the for-profit foster care system.
-
D.
Fowler
Fowler is a surname of English origin borne by numerous notable individuals across fields such as engineering, politics, sports, and the arts.
-
E.
Torey
Torey is a given name, typically used as a variant of names like Tore or Tory.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a54cf8188190b9bd676443418c23 |
completed | April 19, 2026, 9:50 a.m. |
Created at: April 10, 2026, 10:20 a.m.