Triple
T17884721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gen¹³ |
E447171
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Caitlin Fairchild |
—
|
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: Caitlin Fairchild | Statement: [Gen¹³, member, Caitlin Fairchild]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caitlin Fairchild Context triple: [Gen¹³, member, Caitlin Fairchild]
-
A.
Caitlin Fairchild
chosen
Caitlin Fairchild is a super-intelligent, super-strong heroine from WildStorm/DC Comics, best known as a central member of the Gen¹³ team.
-
B.
Caitlin Blackwood
Caitlin Blackwood is a Scottish actress best known for playing the young Amelia Pond in the BBC science fiction series Doctor Who.
-
C.
Emily Cavanaugh
Emily Cavanaugh is a character in the television series "Crossing Jordan," known as a relative of the protagonist, Dr. Jordan Cavanaugh.
-
D.
Samantha Taggart
Samantha Taggart is a strong-willed, street-smart emergency room nurse on the television series "ER," known for her resilience and complex personal relationships.
-
E.
Caitlin Snow
Caitlin Snow is a central character in DC Comics and The Flash TV series, known as a brilliant scientist who becomes the metahuman Killer Frost.
- 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c11530881908ad98fbd0a52b1c3 |
completed | April 19, 2026, 9:10 a.m. |
Created at: April 10, 2026, 10:18 a.m.