Triple
T16623449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heroes Join Forces (Arrowverse) |
E403886
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Caitlin Snow |
E1224042
|
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: Caitlin Snow | Statement: [Heroes Join Forces (Arrowverse), featuresCharacter, Caitlin Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caitlin Snow Context triple: [Heroes Join Forces (Arrowverse), featuresCharacter, Caitlin Snow]
-
A.
Caitlin Snow
chosen
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.
-
B.
Caitlin Carver
Caitlin Carver is an American actress and dancer known for her supporting roles in film and television, including the biographical dark comedy "I, Tonya."
-
C.
Caitlin Caine
Caitlin Caine is the daughter of American rapper and actress Charly Baltimore.
-
D.
Caitlin Blackwood
Caitlin Blackwood is a Scottish actress best known for playing the young Amelia Pond in the BBC science fiction series Doctor Who.
-
E.
Tessa Scott
Tessa Scott is a terminally ill teenage girl who creates and pursues a bold bucket list while confronting love, family, and mortality in the novel and film "Now Is Good."
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754f4f508190a5b4b8511623fcd4 |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d2d802881909abd846cc54f04fc |
completed | May 10, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:17 a.m.