Triple
T15763691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammy Collins |
E382163
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tammy Collins |
E382163
|
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: Tammy Collins | Statement: [Tammy Collins, name, Tammy Collins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tammy Collins Context triple: [Tammy Collins, name, Tammy Collins]
-
A.
Tammy Collins
chosen
Tammy Collins is the wife of Grammy-winning gospel musician and choir director Kirk Franklin, known for her supportive role in his personal life and ministry.
-
B.
Tammy Townsend
Tammy Townsend is an American actress and singer best known for her roles in television series such as "Family Matters" and "K.C. Undercover."
-
C.
Tammy Campbell
Tammy Campbell is the daughter of advertising executive Pete Campbell in the television series "Mad Men."
-
D.
Lori Collins
Lori Collins is a central character in the comedy film "Ted," known as John Bennett’s long-suffering girlfriend who pushes him to grow up and choose between her and his crude, living teddy bear best friend.
-
E.
Tammy Lucas
Tammy Lucas is an American R&B singer and songwriter known for her collaborations with prominent hip-hop artists and producers in the 1990s.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbbd605c8190ae2b1289ae9570c3 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:47 a.m.