Triple
T3269070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carine |
E68597
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Caitlin |
E310926
|
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 | Statement: [Carine, hasRelatedName, Caitlin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caitlin Context triple: [Carine, hasRelatedName, Caitlin]
-
A.
Kaitlin
chosen
Kaitlin is a feminine given name commonly used in English-speaking countries, often considered a variant of Caitlin or Kathleen.
-
B.
Cate
Cate is a given name, often used as a short form of Catherine or Katherine.
-
C.
Cailee
Cailee is a feminine given name most notably borne by American actress Cailee Spaeny.
-
D.
Kaitlyn Dias
Kaitlyn Dias is an American actress best known for voicing the character Riley Andersen in Pixar's animated film "Inside Out."
-
E.
Mia Dolan
Mia Dolan is an aspiring actress in Los Angeles and one of the two central protagonists of the musical film "La La Land."
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafd0eddc8190834a64f6b8e8e9f9 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28efded588190bd6c361e5298b496 |
completed | March 12, 2026, 10:01 a.m. |
Created at: March 8, 2026, 3:09 p.m.