Triple
T5649816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michele |
E124474
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object |
Michelle
Michelle is a common given name, typically the feminine form of Michael, used in many English- and French-speaking countries.
|
E535305
|
NE FINISHED |
How this triple was built (4 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: Michelle | Statement: [Michele, hasSpellingVariant, Michelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Context triple: [Michele, hasSpellingVariant, Michelle]
-
A.
Michelle
Michelle is a Fossil Group watch and accessories brand known for its fashion-forward, feminine designs and luxury-inspired styling.
-
B.
Michelle
Michelle is the resourceful and determined protagonist of the psychological thriller film "10 Cloverfield Lane."
-
C.
Michelle
"Michelle" is a gentle, melodic love song by the Beatles, featured on their 1965 album Rubber Soul and known for its French lyrics and romantic acoustic style.
-
D.
Hilary
Hilary is a given name most notably borne by the influential American philosopher Hilary Putnam.
-
E.
Mary Johnson
Mary Johnson is the impoverished young protagonist of Stephen Crane’s novella "Maggie: A Girl of the Streets," whose tragic life in the slums of New York highlights the brutal effects of poverty and social hypocrisy.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Michelle Triple: [Michele, hasSpellingVariant, Michelle]
Generated description
Michelle is a common given name, typically the feminine form of Michael, used in many English- and French-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Target entity description: Michelle is a common given name, typically the feminine form of Michael, used in many English- and French-speaking countries.
-
A.
Michelle
Michelle is a Fossil Group watch and accessories brand known for its fashion-forward, feminine designs and luxury-inspired styling.
-
B.
Michelle
Michelle is the resourceful and determined protagonist of the psychological thriller film "10 Cloverfield Lane."
-
C.
Michelle
"Michelle" is a gentle, melodic love song by the Beatles, featured on their 1965 album Rubber Soul and known for its French lyrics and romantic acoustic style.
-
D.
Hilary
Hilary is a given name most notably borne by the influential American philosopher Hilary Putnam.
-
E.
Mary Johnson
Mary Johnson is the impoverished young protagonist of Stephen Crane’s novella "Maggie: A Girl of the Streets," whose tragic life in the slums of New York highlights the brutal effects of poverty and social hypocrisy.
- F. None of above. chosen
Provenance (5 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d2ed648190a5152c8668cbda02 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d90c04881908740fb1089c5248a |
completed | March 22, 2026, 8:14 p.m. |
| NEDg | Description generation | batch_69c04edcc0208190bd69b5cce89596f9 |
completed | March 22, 2026, 8:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04ff814b88190ad01844ae2629c6e |
completed | March 22, 2026, 8:24 p.m. |
Created at: March 22, 2026, 3:42 p.m.