Triple
T10285627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashley |
E241218
|
entity |
| Predicate | hasAlternativeSpelling |
P457
|
FINISHED |
| Object | Ashleigh |
E241218
|
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: Ashleigh | Statement: [Ashley, hasAlternativeSpelling, Ashleigh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashleigh Context triple: [Ashley, hasAlternativeSpelling, Ashleigh]
-
A.
Ashleigh Aston Moore
Ashleigh Aston Moore was a Canadian child actress best known for her role as the young Chrissy in the 1995 coming-of-age film "Now and Then."
-
B.
Ashlee
Ashlee is a feminine given name most notably associated with American singer and actress Ashlee Simpson.
-
C.
Ashley
Ashley is a small village and civil parish located within the county of Suffolk in eastern England.
-
D.
Ashley
Ashley is a character featured in the animated children’s series "¡Dos!"
-
E.
Ashley
chosen
Ashley is a given name commonly used in English-speaking countries for both males and females.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b737788190bfadd0d48ad38f5b |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d0b40d081908eb3f7ba24352a42 |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:40 a.m.