Triple
T17113556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regio I Latium et Campania |
E415283
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sinuessa |
E858349
|
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: Sinuessa | Statement: [Regio I Latium et Campania, contains, Sinuessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinuessa Context triple: [Regio I Latium et Campania, contains, Sinuessa]
-
A.
Sinuessa
chosen
Sinuessa was an ancient Roman coastal town in Campania, Italy, known for its strategic location along major roads and its nearby thermal baths.
-
B.
Ein Siniya
Ein Siniya is a small Palestinian village in the central West Bank, known for its rural character and proximity to the town of Birzeit.
-
C.
Kusaila
Kusaila was a 7th-century Berber Christian leader and military commander who led resistance against the early Muslim expansion in North Africa.
-
D.
Toinette
Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
-
E.
Sijilmasa
Sijilmasa was a medieval Moroccan oasis city that flourished as a key commercial hub linking North Africa with sub-Saharan gold and trade networks.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8033840819083e9a506e48c31b4 |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a062d7c81908fe8cdc9e4637168 |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:35 a.m.