Triple
T23044131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Reiger |
E573826
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Latka Gravas |
—
|
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: Latka Gravas | Statement: [Alex Reiger, hasColleague, Latka Gravas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Latka Gravas Context triple: [Alex Reiger, hasColleague, Latka Gravas]
-
A.
Latka Gravas
chosen
Latka Gravas is a lovable, eccentric immigrant mechanic known for his childlike innocence and quirky speech on the sitcom "Taxi."
-
B.
Vaida
Vaida is a small settlement located in Rae Parish in northern Estonia.
-
C.
Laima
Laima is a major Baltic goddess associated with fate, luck, and childbirth in traditional Latvian and Lithuanian mythology.
-
D.
Petras
Petras is an important Minoan archaeological site near Sitia on the island of Crete, known for its palace complex and rich Bronze Age remains.
-
E.
Sarma Melngailis
Sarma Melngailis is a former New York City restaurateur and co-founder of the vegan restaurant Pure Food and Wine who became widely known after a high-profile fraud scandal and the Netflix documentary "Bad Vegan."
- 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_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18517083c8190a0850da5440e0a73 |
completed | April 29, 2026, 4:12 a.m. |
Created at: April 17, 2026, 3:54 p.m.