Triple
T8544556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marillion |
E202284
|
entity |
| Predicate | notableSingle |
P3283
|
FINISHED |
| Object | Kayleigh |
E423831
|
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: Kayleigh | Statement: [Marillion, notableSingle, Kayleigh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kayleigh Context triple: [Marillion, notableSingle, Kayleigh]
-
A.
Kayely
Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
-
B.
Hayley
Hayley is a Canadian former ice hockey player widely regarded as one of the greatest female hockey players of all time.
-
C.
Hayley
Hayley is a feminine given name commonly used in English-speaking countries, often associated with meanings related to hay meadows or clearings.
-
D.
Marleigh
Marleigh is a given name, typically a modern feminine variant of the name Marley.
-
E.
Kaylee
chosen
Kaylee is a feminine given name, often considered a modern, creative spelling of names like Cailee, Kayleigh, or Kayla.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e4e21c8190afcbca73713a5fa8 |
completed | March 31, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6db3eef08190934f5b42807ad769 |
completed | April 2, 2026, 1:23 p.m. |
Created at: March 30, 2026, 6:18 p.m.