Triple
T21865239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Procas |
E539866
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | Numitor |
—
|
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: Numitor | Statement: [Procas, successor, Numitor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Numitor Context triple: [Procas, successor, Numitor]
-
A.
Numitor
chosen
Numitor is a legendary king of Alba Longa in Roman mythology, best known as the deposed ruler whose grandsons Romulus and Remus ultimately restored his throne.
-
B.
Numa Pompilius
Numa Pompilius was the legendary second king of Rome, renowned for his wisdom, piety, and for establishing many of Rome’s early religious and legal institutions.
-
C.
Romolo
Romolo is the middle name of Albert R. Broccoli, the influential American film producer best known for co-producing the James Bond movie series.
-
D.
Romolo
Romolo is a station on Milan's Metro system, serving Line 2 in the city of Milan, Italy.
-
E.
Romulus
Romulus is a city in Michigan best known as the location of Detroit Metropolitan Wayne County Airport, one of the state's major transportation hubs.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63e70c08190a9ba90c47c4060d4 |
completed | April 28, 2026, 3:46 p.m. |
Created at: April 16, 2026, 6:56 p.m.