Triple
T23156917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Long |
E578464
|
entity |
| Predicate | hasDiminutiveOf |
P456
|
FINISHED |
| Object |
Michael
Michael is a common male given name of Hebrew origin, widely used in many cultures and often shortened to forms like Mike.
|
E21023
|
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: Michael | Statement: [Mike Long, hasDiminutiveOf, Michael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Context triple: [Mike Long, hasDiminutiveOf, Michael]
-
A.
John
John is the given name of John Houseman, the Romanian-born British-American actor and producer known for his work in film, theater, and radio.
-
B.
John
John is the given first name of Jack-Jack Parr, the infant superhero character from Pixar's "The Incredibles" franchise.
-
C.
John
John VI, Duke of Brittany, was a 15th-century Breton ruler known for consolidating ducal power and navigating the complex politics between France and England during the Hundred Years' War.
-
D.
John
John is the given name of John Adams, the second president of the United States and a prominent Founding Father.
-
E.
John
John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz.
- 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: Michael Triple: [Mike Long, hasDiminutiveOf, Michael]
Generated description
Michael is a common male given name of Hebrew origin, widely used in many cultures and often shortened to forms like Mike.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Target entity description: Michael is a common male given name of Hebrew origin, widely used in many cultures and often shortened to forms like Mike.
-
A.
Michael
chosen
Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
-
B.
Michael
Michael is a historical warship, likely a naval vessel named after the given male name Michael.
-
C.
Michael
Michael is the Christian baptismal name taken by Boris I, the 9th-century ruler who converted Bulgaria to Christianity and helped establish the Bulgarian Orthodox Church.
-
D.
Michael
Michael is the first name of Detective Michael Hitchcock, a bumbling yet endearing police detective character from the comedy series "Brooklyn Nine-Nine."
-
E.
Michael
Michael is the central protagonist of the card game Dominion’s narrative setting, around whom the game’s implied story of kingdom-building and power struggles revolves.
- F. None of above.
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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efe1b0081908e81b757d64c067c |
completed | April 29, 2026, 4:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c309e4518819095eb3d8a6f6a0808 |
completed | May 19, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_6a0c332f5ef08190ab7f6536eb719e04 |
completed | May 19, 2026, 9:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c374ded1c8190b1d5c7a3ab521cf9 |
completed | May 19, 2026, 10:11 a.m. |
Created at: April 17, 2026, 4:01 p.m.