Triple
T21248475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vénissieux |
E523678
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Batroun |
—
|
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: Batroun | Statement: [Vénissieux, hasTwinTown, Batroun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batroun Context triple: [Vénissieux, hasTwinTown, Batroun]
-
A.
Batroun
chosen
Batroun is a historic coastal city in northern Lebanon known for its Phoenician heritage, old souks, and popular Mediterranean beaches.
-
B.
Batroun District
Batroun District is an administrative district in northern Lebanon known for its coastal towns, historic sites, and wine-producing villages.
-
C.
Gabès
Gabès is a coastal city in southeastern Tunisia known as an oasis on the Gulf of Gabès and a strategic location in World War II.
-
D.
Zarzis
Zarzis is a coastal town in southeastern Tunisia known for its Mediterranean beaches, olive groves, and role as a regional fishing and trading center.
-
E.
Kfarsaroun
Kfarsaroun is a village located in the Koura District of northern Lebanon, known for its traditional rural character and Mediterranean setting.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359b756c819085480ca4174c53c2 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:56 p.m.