Triple
T4456233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Homer |
E97730
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Mike |
E21023
|
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: Mike | Statement: [Mike Homer, hasGivenName, Mike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Context triple: [Mike Homer, hasGivenName, Mike]
-
A.
Michael
chosen
Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
-
B.
Mitch
Mitch is a masculine given name, often used as a short form of Mitchell.
-
C.
Micheal
Micheal is a given name, typically a variant spelling of the more common name Michael.
-
D.
Kevin
Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
-
E.
Kevin
Kevin is the young boy protagonist of the 1981 fantasy adventure film "Time Bandits," who joins a group of time-traveling dwarfs on a series of historical escapades.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3564216b081908c41109100b36862 |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6282743e08190a2c84f3b80c6d260 |
completed | March 15, 2026, 3:31 a.m. |
Created at: March 12, 2026, 11:33 p.m.