Triple
T20598495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terry Gilkyson |
E506111
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Terry |
—
|
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: Terry | Statement: [Terry Gilkyson, givenName, Terry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terry Context triple: [Terry Gilkyson, givenName, Terry]
-
A.
Terry
Terry is a central character associated with Calvero, likely someone he mentors or supports during a pivotal period in their story.
-
B.
Terry
Terry is a surname of English origin borne by various notable individuals, including military figures such as Alfred Terry.
-
C.
Terry
chosen
Terry is a masculine given name commonly used in English-speaking countries, often as a diminutive of names like Terence or Theresa.
-
D.
Terry
Terry is the pet dog adopted by Liz Lemon on the television series "30 Rock."
-
E.
Terry
Terry is a character from the short film "I Love Sarah Jane," which follows a group of kids navigating adolescence and survival in a zombie-infested world.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1e251c8190926dafe1402eb63c |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:40 a.m.