Triple
T2322649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabitha King |
E48215
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tabitha |
E246507
|
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: Tabitha | Statement: [Tabitha King, givenName, Tabitha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabitha Context triple: [Tabitha King, givenName, Tabitha]
-
A.
Tabitha
chosen
Tabitha is a feminine given name of Aramaic origin, traditionally interpreted to mean "gazelle" and associated with grace and beauty.
-
B.
Tabitha Grant
Tabitha Grant is the daughter of British actor Hugh Grant and his former partner Tinglan Hong.
-
C.
Tabitha King
Tabitha King is an American author known for her novels and short stories, and as the wife of writer Stephen King.
-
D.
Tessa
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
-
E.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc645bac081908c0b161d0ca99aaf |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea8786d508190aac531a88fc5076f |
completed | March 9, 2026, 11:01 a.m. |
Created at: March 4, 2026, 7:49 p.m.