Triple
T22826678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrison |
E565678
|
entity |
| Predicate | derivedFromGivenName |
P17
|
FINISHED |
| Object | Harry |
—
|
NE NERFINISHED |
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: Harry | Statement: [Harrison, derivedFromGivenName, Harry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Context triple: [Harrison, derivedFromGivenName, Harry]
-
A.
Harry
chosen
Harry is a masculine given name of English origin commonly used in many English-speaking countries.
-
B.
Harry
Harry is the given name of British Army officer Reginald Dyer, infamous for ordering the 1919 Jallianwala Bagh massacre in Amritsar, India.
-
C.
Harry
Harry is a central character in the film "All of Us Strangers," serving as the protagonist's enigmatic romantic partner whose presence deeply shapes the story’s emotional journey.
-
D.
Harry
Harry is the given name of Harry W. Gerstad, an American film editor known for his work in mid-20th-century cinema.
-
E.
Harry
Harry is the given name of Harry K. Thaw, the American millionaire best known for his 1906 murder of architect Stanford White in a scandalous crime of passion.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2832b8819091c1dfd2cd598b90 |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:34 p.m.